Results for 'Prediction'

232 found
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  1.  92
    Prediction Versus Accommodation in Economics.Robert Northcott - 2019 - Journal of Economic Methodology 26 (1):59-69.
    Should we insist on prediction, i.e. on correctly forecasting the future? Or can we rest content with accommodation, i.e. empirical success only with respect to the past? I apply general considerations about this issue to the case of economics. In particular, I examine various ways in which mere accommodation can be sufficient, in order to see whether those ways apply to economics. Two conclusions result. First, an entanglement thesis: the need for prediction is entangled with the methodological role (...)
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  2. Experience and Prediction.Hans Reichenbach - 1938 - University of Chicago Press.
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  3. Parkinson’s Disease Prediction Using Artificial Neural Network.Ramzi M. Sadek, Salah A. Mohammed, Abdul Rahman K. Abunbehan, Abdul Karim H. Abdul Ghattas, Majed R. Badawi, Mohamed N. Mortaja, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (1):1-8.
    Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in identifying (...)
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  4. Prediction, Authority, and Entitlement in Shared Activity.Abraham Sesshu Roth - 2014 - Noûs 48 (4):626-652.
    Shared activity is often simply willed into existence by individuals. This poses a problem. Philosophical reflection suggests that shared activity involves a distinctive, interlocking structure of intentions. But it is not obvious how one can form the intention necessary for shared activity without settling what fellow participants will do and thereby compromising their agency and autonomy. One response to this problem suggests that an individual can have the requisite intention if she makes the appropriate predictions about fellow participants. I argue (...)
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  5.  75
    The Body as Laboratory: Prediction-Error Minimization, Embodiment, and Representation.Christopher Burr & Max Jones - 2016 - Philosophical Psychology 29 (4):586-600.
    In his paper, Jakob Hohwy outlines a theory of the brain as an organ for prediction-error minimization, which he claims has the potential to profoundly alter our understanding of mind and cognition. One manner in which our understanding of the mind is altered, according to PEM, stems from the neurocentric conception of the mind that falls out of the framework, which portrays the mind as “inferentially-secluded” from its environment. This in turn leads Hohwy to reject certain theses of embodied (...)
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  6. Explanatory Pluralism: An Unrewarding Prediction Error for Free Energy Theorists.Matteo Colombo & Cory Wright - 2017 - Brain and Cognition 112:3–12.
    Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity—the anhedonia, incentive salience, and reward prediction error hypotheses—we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB are unwarranted. More (...)
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  7. Prediction in Selectionist Evolutionary Theory.Rasmus Grønfeldt Winther - 2009 - Philosophy of Science 76 (5):889-901.
    Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.
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  8. Experiential Fantasies, Prediction, and Enactive Minds.Michael David Kirchhoff - 2015 - Journal of Consciousness Studies 22 (3-4):68-92.
    A recent surge of work on prediction-driven processing models--based on Bayesian inference and representation-heavy models--suggests that the material basis of conscious experience is inferentially secluded and neurocentrically brain bound. This paper develops an alternative account based on the free energy principle. It is argued that the free energy principle provides the right basic tools for understanding the anticipatory dynamics of the brain within a larger brain-body-environment dynamic, viewing the material basis of some conscious experiences as extensive--relational and thoroughly world-involving.
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  9. Stereotypes, Theory of Mind, and the Action–Prediction Hierarchy.Evan Westra - 2019 - Synthese 196 (7):2821-2846.
    Both mindreading and stereotyping are forms of social cognition that play a pervasive role in our everyday lives, yet too little attention has been paid to the question of how these two processes are related. This paper offers a theory of the influence of stereotyping on mental-state attribution that draws on hierarchical predictive coding accounts of action prediction. It is argued that the key to understanding the relation between stereotyping and mindreading lies in the fact that stereotypes centrally involve (...)
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  10. Ramsey and Joyce on Deliberation and Prediction.Yang Liu & Huw Price - 2020 - Synthese 197:4365-4386.
    Can an agent deliberating about an action A hold a meaningful credence that she will do A? 'No', say some authors, for 'Deliberation Crowds Out Prediction' (DCOP). Others disagree, but we argue here that such disagreements are often terminological. We explain why DCOP holds in a Ramseyian operationalist model of credence, but show that it is trivial to extend this model so that DCOP fails. We then discuss a model due to Joyce, and show that Joyce's rejection of DCOP (...)
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  11. Prediction and Topological Models in Neuroscience.Bryce Gessell, Matthew Stanley, Benjamin Geib & Felipe De Brigard - forthcoming - In Fabrizio Calzavarini & Marco Viola (eds.), Neural Mechanisms: New challenges in the philosophy of neuroscience. Springer.
    In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological (...)
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  12. Prediction in General Relativity.C. McCoy - 2017 - Synthese 194 (2):491-509.
    Several authors have claimed that prediction is essentially impossible in the general theory of relativity, the case being particularly strong, it is said, when one fully considers the epistemic predicament of the observer. Each of these claims rests on the support of an underdetermination argument and a particular interpretation of the concept of prediction. I argue that these underdetermination arguments fail and depend on an implausible explication of prediction in the theory. The technical results adduced in these (...)
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  13. The Prediction of Future Behavior: The Empty Promises of Expert Clinical and Actuarial Testimony.Andrés Páez - 2016 - Teoria Jurídica Contemporânea 1 (1):75-101.
    Testimony about the future dangerousness of a person has become a central staple of many judicial processes. In settings such as bail, sentencing, and parole decisions, in rulings about the civil confinement of the mentally ill, and in custody decisions in a context of domestic violence, the assessment of a person’s propensity towards physical or sexual violence is regarded as a deciding factor. These assessments can be based on two forms of expert testimony: actuarial or clinical. The purpose of this (...)
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  14. State of the Field: Why Novel Prediction Matters.Heather Douglas & P. D. Magnus - 2013 - Studies in History and Philosophy of Science Part A 44 (4):580-589.
    There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential (...)
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  15.  47
    Prediction, History and Political Science.Robert Northcott - forthcoming - In Harold Kincaid & Jeroen Van Bouwel (eds.), Oxford Handbook of Philosophy of Political Science. Oxford University Press.
    To succeed, political science usually requires either prediction or contextual historical work. Both of these methods favor explanations that are narrow-scope, applying to only one or a few cases. Because of the difficulty of prediction, the main focus of political science should often be contextual historical work. These epistemological conclusions follow from the ubiquity of causal fragility, under-determination, and noise. They tell against several practices that are widespread in the discipline: wide-scope retrospective testing, such as much large-n statistical (...)
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  16. The Risk GP Model: The Standard Model of Prediction in Medicine.Jonathan Fuller & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 54:49-61.
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  17. Against the Epistemic Value of Prediction Over Accommodation.Robin Collins - 1994 - Noûs 28 (2):210-224.
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  18. Motor Experience Interacts with Effector Information During Action Prediction.Lincoln Colling, William Thompson & John Sutton - 2013 - Proceedings of the 35th Annual Conference of the Cognitive Science Society:2082-2087.
    Recent theory suggests that action prediction relies of a motor emulation mechanism that works by mapping observed actions onto the observer action system so that predictions can be generated using that same predictive mechanisms that underlie action control. This suggests that action prediction may be more accurate when there is a more direct mapping between the stimulus and the observer. We tested this hypothesis by comparing prediction accuracy for two stimulus types. A mannequin stimulus which contained information (...)
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  19.  17
    MPG Prediction Using Artificial Neural Network.Yara Ibrahim Al Barsh, Maram Khaled Duhair, Hassan Jassim Ismail, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (11):7-16.
    Abstract: During the course of this research, imposing the training of an artificial neural network to predicate the MPG rate for present thru forthcoming automobiles in the foremost relatively accurate evaluation for the approximated number which foresight the actual number to help through later design and manufacturing of later automobile, by training the ANN to accustom to the relationship between the skewing of each later stated attributes, the set of mathematical combination of the sequences that could be excavate the Miles (...)
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  20. Forgery: Prediction's Vile Twin.Joachim L. Dagg - 2003 - Science 302:783-784.
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  21. Prediction in Epidemiology and Medicine.Jonathan Fuller, Alex Broadbent & Luis J. Flores - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences.
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  22. "Deliberation and Prediction: It's Complicated".Vavova Katia - 2016 - Episteme 13 (4):529-538.
    Alan Hájek launches a formidable attack on the idea that deliberation crowds out prediction – that when we are deliberating about what to do, we cannot rationally accommodate evidence about what we are likely to do. Although Hájek rightly diagnoses the problems with some of the arguments for the view, his treatment falls short in crucial ways. In particular, he fails to consider the most plausible version of the view, the best argument for it, and why anyone would ever (...)
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  23.  31
    Breast Cancer Prediction Using JNN.Mohammed Abdul Hay Abu Bakr, Haitham Maher Al-Attar, Nader Kamal Mahra & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (10):1-8.
    Abstract- Breast Cancer is mostly identified amongst women and is a main reason for increasing the rate of mortality amongst women. Diagnosis of breast cancer takes time and due to the importance of the topic, it is necessary to develop a system that can automatically diagnose breast cancer in its early stages. Many Machine Learning Algorithms have been used for the detection breast cancer. The Wisconsin Breast Cancer Dataset has been used which contains 699 samples and 10 features. The paper (...)
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  24. Delusions: Between Phenomenology and Prediction.Przemysław Nowakowski - 2014 - Avant: Trends in Interdisciplinary Studies (3/2014):11-16.
    One of the leading and central figures in research on delusions, Max Coltheart, presents and summarises his heretofore work in a short text. Miyazono and Bortolotti present an interesting argument aimed at the charges against the doxastic concept of delusions. Adams, Brown and Friston showcase a predictive-Bayesian concept of delusions. Young criticizes the current changes in the two-factor account of delusions and argues that the role of experience should not be dismissed within it. Kapusta presents an interesting, phenomenological approach to (...)
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  25.  58
    Books’ Rating Prediction Using Just Neural Network.Alaa Mazen Maghari, Iman Ali Al-Najjar, Said Jamil Al-Laqtah & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (10):17-22.
    Abstract: The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of (...)
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  26.  15
    Low Birth Weight Prediction Using JNN.Osama Salah El-Din Al-Madhoun, Afnan Omar Abu Hasira, Soha Ahmed Hegazy & Samy S. Abu-Naser - 2020 - International Journal of Academic Health and Medical Research (IJAHMR) 4 (11):8-14.
    Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict Birth Weight. A number of factors were identified that may affect birth weight. Factors such as smoke, race, age, weight (lbs) at last menstrual period, hypertension, uterine irritability, number of physician visits in 1st trimester, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some birth cases in hospitals. The (...)
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  27.  48
    Presence of Amphibian Species Prediction Using Features Obtained From GIS and Satellite Images.Nadia Shaker Habib, Omar Kamal Abu Maghasib, Ahmed Rashad Al-Ghazali, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (11):13-22.
    The establishment of the transport infrastructure is usually preceded by an EIA procedure, which should determine amphibian breeding sites and migration routes. However, evaluation is very difficult due to the large number of habitats spread over a vast area and the limited time available for field work. An artificial Neural Network (ANN) is proposed for predicting the presence of amphibians species near the water reservoirs based on features obtained from GIS systems and satellite images. The dataset collected from UCI Machine (...)
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  28.  24
    Antibiotic Susceptibility Prediction Using JNN.Ahmed Jabara Abu Oriban, Shaima Naji Abdel-Al, Nourhan Abdel Moneim Fouda & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (11):1-6.
    Abstract: In this research, an Artificial Neural Network (ANN) model was developed and validated to predict efficiency of antibiotics in treating various bacteria types. Attributes that were taken in account are: organism name, specimen type, and antibiotic name as input and susceptibility as an output. A model based on one input layer, one hidden layer, and one output layer concept topology was developed and trained using a data from Queensland government's website. The evaluation shows that the proposed ANN model using (...)
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  29.  61
    Breast Cancer Diagnosis and Survival Prediction Using JNN.Mohammed Ziyad Abu Shawarib, Ahmed Essam Abdel Latif, Bashir Essam El-Din Al-Zatmah & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (10):23-30.
    Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on Haberman’s (...)
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  30.  23
    More Connection and Less Prediction Please: Applying a Relationship Focus in Protected Area Planning and Management.Robert G. Dvorak & Jeffrey Brooks - 2013 - Journal of Park and Recreation Administration 31 (3):5-22.
    Integrating the concept of place meanings into protected area management has been difficult. Across a diverse body of social science literature, challenges in the conceptualization and application of place meanings continue to exist. However, focusing on relationships in the context of participatory planning and management allows protected area managers to bring place meanings into professional judgment and practice. This paper builds on work that has outlined objectives and recommendations for bringing place meanings, relationships, and lived experiences to the forefront of (...)
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  31.  30
    Children’s Reasoning About the Efficiency of Others’ Actions: The Development of Rational Action Prediction.Gökhan Gönül & Markus Paulus - 2021 - Journal of Experimental Child Psychology 204 (105035).
    The relative efficiency of an action is a central criterion in action control and can be used to predict others’ behavior. Yet, it is unclear when the ability to predict on and reason about the efficiency of others’ actions develops. In three main and two followup studies, 3- to 6-year-old children (n = 242) were confronted with vignettes in which protagonists could take a short (efficient) path or a long path. Children predicted which path the protagonist would take and why (...)
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  32.  9
    Children’s Reasoning About the Efficiency of Others’ Actions: The Development of Rational Action Prediction.Gökhan Gönül & Markus Paulus - 2021 - Journal of Experimental Child Psychology 105035 (204).
    The relative efficiency of an action is a central criterion in action control and can be used to predict others’ behavior. Yet, it is unclear when the ability to predict on and reason about the efficiency of others’ actions develops. In three main and two follow-up studies, 3- to 6-year-old children (n = 242) were confronted with vignettes in which protagonists could take a short (efficient) path or a long path. Children predicted which path the protagonist would take and why (...)
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  33. Avoiding Reification: Heuristic Effectiveness of Mathematics and the Prediction of the Omega Minus Particle.Michele Ginammi - 2016 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 53:20-27.
    According to Steiner (1998), in contemporary physics new important discoveries are often obtained by means of strategies which rely on purely formal mathematical considerations. In such discoveries, mathematics seems to have a peculiar and controversial role, which apparently cannot be accounted for by means of standard methodological criteria. M. Gell-Mann and Y. Ne׳eman׳s prediction of the Ω− particle is usually considered a typical example of application of this kind of strategy. According to Bangu (2008), this prediction is apparently (...)
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  34. ANN for Parkinson’s Disease Prediction.Salah Sadek, Abdul Mohammed, Abdul Karim Abunbehan, Majed Abdul Ghattas & Mohamed Badawi - 2020 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (1):1-7.
    Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in identifying (...)
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  35. A Meta-Doomsday Argument: Uncertainty About the Validity of the Probabilistic Prediction of the End of the World.Alexey Turchin - manuscript
    Abstract: Four main forms of Doomsday Argument (DA) exist—Gott’s DA, Carter’s DA, Grace’s DA and Universal DA. All four forms use different probabilistic logic to predict that the end of the human civilization will happen unexpectedly soon based on our early location in human history. There are hundreds of publications about the validity of the Doomsday argument. Most of the attempts to disprove the Doomsday Argument have some weak points. As a result, we are uncertain about the validity of DA (...)
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  36.  77
    Artificial Neural Network for Mushroom Prediction.Kamel Jamal Dawood, Mohamed Hussam Zaqout, Riad Mohammed Salem & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (10):9-17.
    Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the dataset. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether mushroom is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JNN tool was used for training and validating the (...)
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  37. Models, Brains, and Scientific Realism.Fabio Sterpetti - 2006 - In Lorenzo Magnani & Claudia Casadio (eds.), Model Based Reasoning in Science and Technology. Logical, Epistemological, and Cognitive Issues. Springer. pp. 639-661.
    Prediction Error Minimization theory (PEM) is one of the most promising attempts to model perception in current science of mind, and it has recently been advocated by some prominent philosophers as Andy Clark and Jakob Hohwy. Briefly, PEM maintains that “the brain is an organ that on aver-age and over time continually minimizes the error between the sensory input it predicts on the basis of its model of the world and the actual sensory input” (Hohwy 2014, p. 2). An (...)
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  38. On Predicting.Fabrizio Cariani - forthcoming - Ergo: An Open Access Journal of Philosophy.
    I propose an account of the speech act of prediction that denies that the contents of prediction must be about the future and illuminates the relation between prediction and assertion. My account is a synthesis of two ideas: (i) that what is in the future in prediction is the time of discovery and (ii) that, as Benton and Turri recently argued, prediction is best characterized in terms of its constitutive norms.
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  39.  64
    When Are Purely Predictive Models Best?Robert Northcott - 2017 - Disputatio 9 (47):631-656.
    Can purely predictive models be useful in investigating causal systems? I argue ‘yes’. Moreover, in many cases not only are they useful, they are essential. The alternative is to stick to models or mechanisms drawn from well-understood theory. But a necessary condition for explanation is empirical success, and in many cases in social and field sciences such success can only be achieved by purely predictive models, not by ones drawn from theory. Alas, the attempt to use theory to achieve explanation (...)
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  40. The Self‐Evidencing Brain.Jakob Hohwy - 2014 - Noûs 48 (1).
    An exciting theory in neuroscience is that the brain is an organ for prediction error minimization (PEM). This theory is rapidly gaining influence and is set to dominate the science of mind and brain in the years to come. PEM has extreme explanatory ambition, and profound philosophical implications. Here, I assume the theory, briefly explain it, and then I argue that PEM implies that the brain is essentially self-evidencing. This means it is imperative to identify an evidentiary boundary between (...)
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  41. Heart of DARCness.Yang Liu & Huw Price - 2019 - Australasian Journal of Philosophy 97 (1):136-150.
    There is a long-standing disagreement in the philosophy of probability and Bayesian decision theory about whether an agent can hold a meaningful credence about an upcoming action, while she deliberates about what to do. Can she believe that it is, say, 70% probable that she will do A, while she chooses whether to do A? No, say some philosophers, for Deliberation Crowds Out Prediction (DCOP), but others disagree. In this paper, we propose a valid core for DCOP, and identify (...)
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  42. The Folk Psychological Spiral: Explanation, Regulation, and Language.Kristin Andrews - 2015 - Southern Journal of Philosophy 53 (S1):50-67.
    The view that folk psychology is primarily mindreading beliefs and desires has come under challenge in recent years. I have argued that we also understand others in terms of individual properties such as personality traits and generalizations from past behavior, and in terms of group properties such as stereotypes and social norms (Andrews 2012). Others have also argued that propositional attitude attribution isn’t necessary for predicting others’ behavior, because this can be done in terms of taking Dennett’s Intentional Stance (Zawidzki (...)
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  43. Folk Psychology is Not a Predictive Device.Adam Morton - 1996 - Mind 105 (417):119-37.
    I argue that folk psychology does not serve the purpose of facilitating prediction of others' behaviour but if facilitating cooperative action. (See my subsequent book *The Importance of Being Understood*.
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  44. Lesser Degrees of Explanation: Some Implications of F.A. Hayek’s Methodology of Sciences of Complex Phenomena.Scott Scheall - 2015 - Erasmus Journal for Philosophy and Economics 8 (1):42-60.
    From the early-1950s on, F.A. Hayek was concerned with the development of a methodology of sciences that study systems of complex phenomena. Hayek argued that the knowledge that can be acquired about such systems is, in virtue of their complexity (and the comparatively narrow boundaries of human cognitive faculties), relatively limited. The paper aims to elucidate the implications of Hayek’s methodology with respect to the specific dimensions along which the scientist’s knowledge of some complex phenomena may be limited. Hayek’s fallibilism (...)
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  45.  38
    ANN Model for Predicting Protein Localization Sites in Cells.Mohammed Nafez Abu Samra, Bilal Ezz El-Din Abed, Hossam Abdel Nasser Zaqout & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (9):43-50.
    To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and (...)
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  46. Opinion Polling and Election Predictions.Robert Northcott - 2015 - Philosophy of Science 82 (5):1260-1271.
    Election prediction by means of opinion polling is a rare empirical success story for social science. I examine the details of a prominent case, drawing two lessons of more general interest: Methodology over metaphysics. Traditional metaphysical criteria were not a useful guide to whether successful prediction would be possible; instead, the crucial thing was selecting an effective methodology. Which methodology? Success required sophisticated use of case-specific evidence from opinion polling. The pursuit of explanations via general theory or causal (...)
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  47.  13
    Artificial Neural Network for Lung Cancer Detection.Ola Mohammed Abu Kweik, Mohammed Atta Abu Hamid, Samer Osama Sheqlieh, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (11):1-7.
    Abstract: The effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The dataset is collected from the data world website. In this paper, we proposed an Artificial Neural Network for detecting whether lung cancer is found or not in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, (...)
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  48. Popper e o problema da predição prática.Eros Moreira De Carvalho - 2011 - Analytica (Rio) 15 (2):123-146.
    The problem of rational prediction, launched by Wesley Salmon, is without doubt the Achilles heel of the critical method defended by Popper. In this paper, I assess the response given both by Popper and by the popperian Alan Musgrave to this problem. Both responses are inadequate and thus the conclusion of Salmon is reinforced: without appeal to induction, there is no way to make of the practical prediction a rational action. Furthermore, the critical method needs to be vindicated (...)
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  49. Statistical Inference and the Plethora of Probability Paradigms: A Principled Pluralism.Mark L. Taper, Gordon Brittan Jr & Prasanta S. Bandyopadhyay - manuscript
    The major competing statistical paradigms share a common remarkable but unremarked thread: in many of their inferential applications, different probability interpretations are combined. How this plays out in different theories of inference depends on the type of question asked. We distinguish four question types: confirmation, evidence, decision, and prediction. We show that Bayesian confirmation theory mixes what are intuitively “subjective” and “objective” interpretations of probability, whereas the likelihood-based account of evidence melds three conceptions of what constitutes an “objective” probability.
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  50. Review of Kristin Andrews' Do Apes Read Minds? Toward a New Folk Psychology[REVIEW]Neil Van Leeuwen - 2013 - Notre Dame Philosophical Reviews 4.
    Kristin Andrews proposes a new framework for thinking about folk psychology, which she calls Pluralistic Folk Psychology. Her approach emphasizes kinds of psychological prediction and explanation that don't rest on propositional attitude attribution. Here I review some elements of her theory and find that, although the approach is very promising, there's still work to be done before we can conclude that the manners of prediction and explanation she identifies don't involve implicit propositional attitude attribution.
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