English grammar error correction algorithm refers to the use of computer programming technology to automatically recognize and correct the grammar errors contained in English text written by nonnative language learners. Classification model is the core of machine learning and data mining, which can be applied to extracting information from English text data and constructing a reliable grammar correction method. On the basis of summarizing and analyzing previous research works, this paper expounded the research status and significance of English (...) grammar error correction algorithm, elaborated the development background, current status, and future challenges of the classification model, introduced the methods and principles of feature extraction method and dynamic residual structure, constructed a basic model for English grammar error correction based on the classification model, analyzed the classification model and translation model of English grammar error correction, proposed the English grammar error correction algorithm based on the classification model, performed the analyses of the model architecture and model optimizer of the grammar error correction algorithm, and finally conducted a simulation experiment and its result analysis. The study results show that, with the continuous increase of training samples and the continuous progress of learning process, the proposed English grammar error correction algorithm based on the classification model will continue to increase its classification accuracy, further refine its recognition rules, and gradually improve correction efficiency, thereby reducing processing time, saving storage space, and streamlining processing flow. The study results of this paper provide a certain reference for the further research on English grammar error correction algorithm based on the classification model. (shrink)

Within the field of didactics of second language teaching, it is believed that phonic errors cannot be completely corrected due to the significant influence of L1. However, improving the processes of acquisition of an L2 implies learning pronunciation properly. Given the importance of pronunciation for communication, it is necessary to deeply know the nature of phonic errors, which requires a specific classification aimed to describe, classify and categorize them. This article is intended to test the validity and (...) efficiency of the taxonomy developed in the project AACFELE. To accomplish our objective we: a) collected the most significant phonic errors made by learners of Spanish from nine different nationalities and b) categorized those errors. As a result, we found that the classification entails plenty of trouble caused by the impossibility of marking the boundaries of the numerous phenomena involved in the pronunciation of a sound; that is why we considered the need of redefining some of the suggested categories and assessed the adequacy of maintaining other ones less useful. Despite these circumstances, the most significant outcome was the reliable proof that the taxonomy AACFELE allowed us to label and describe diverse phonic errors using common criteria, which represents the first step to accurately study phonic acquisition of a foreign language. (shrink)

. Network data analysis helps in capturing node usage behavior. Existing algorithms use reduced feature set to manage high runtime complexity. Ignoring features may increase classification errors. This paper presents a model, allowing classification of network traffic, while considering all the relevant features. Learning phase partitions training sample on values of the respective features. This creates equivalence classes related to m features. During classification, each feature value of the test instance results in picking one set from (...) equivalence class generated during learning. Algorithm captures new behavior in semi-supervised incremental learning mode. For problems having m features and n training samples the model has incremental learning complexity of and average classification complexity is of the order. (shrink)

Nowadays, lung cancer is one of the most dangerous diseases that require early diagnosis. Artificial intelligence has played an essential role in the medical field in general and in analyzing medical images and diagnosing diseases in particular, as it can reduce human errors that can occur with the medical expert when analyzing medical image. In this research study, we have done a systematic survey of the research published during the last 5 years in the diagnosis of lung cancer (...) class='Hi'>classification of lung nodules in 4 reliable databases, and we selected 50 research paper using systematic literature review. The goal of this review work is to provide a concise overview of recent advancements in lung cancer diagnosis issues by machine learning and deep learning algorithms. This article summarizes the present state of knowledge on the subject. Addressing the findings offered in recent research publications gives the researchers a better grasp of the topic. We checked all the characteristics, such as challenges, recommendations for future work were analyzed in detail, and the published datasets and their source were presented to facilitate the researchers’ access to them and use it to develop the results achieved previously. (shrink)

Multiple studies show that periodic reanalysis of genomic test results held by clinical laboratories delivers significant increases in overall diagnostic yield. However, while there is a widespread consensus that implementing routine reanalysis procedures is highly desirable, there is an equally widespread understanding that routine reanalysis of individual patient results is not presently feasible to perform for all patients. Instead, researchers, geneticists and ethicists are beginning to turn their attention to one part of reanalysis—reinterpretation of previously classified variants—as a means of (...) achieving similar ends to large-scale individual reanalysis but in a more sustainable manner. This has led some to ask whether the responsible implementation of genomics in healthcare requires that diagnostic laboratories routinely reinterpret their genomic variant classifications and reissue patient reports in the case of materially relevant changes. In this paper, we set out the nature and scope of any such obligation, and analyse some of the main ethical considerations pertaining to a putative duty to reinterpret. We discern and assess three potential outcomes of reinterpretation—upgrades, downgrades and regrades—in light of ongoing duties of care, systemic error risks and diagnostic equity. We argue against the existence of any general duty to reinterpret genomic variant classifications, yet we contend that a suitably restricted duty to reinterpret ought to be recognised, and that the responsible implementation of genomics into healthcare must take this into account. (shrink)

Systems with human-centered artificial intelligence are always as good as their ability to consider their users’ context when making decisions. Research on identifying people’s everyday activities has evolved rapidly, but little attention has been paid to recognizing both the activities themselves and the motions they make during those tasks. Automated monitoring, human-to-computer interaction, and sports analysis all benefit from Web 4.0. Every sport has gotten its move, and every move is not known to everyone. In ice hockey, every move cannot (...) be monitored by the referee. Here, Convolution Neural Network-based Real-Time Image Processing Framework (CNN-RTIPF) is introduced to classify every move in Ice Hockey. CNN-RTIPF can reduce the challenges in monitoring the player’s move individually. The image of every move is captured and compared with the trained data in CNN. These real-time captured images are processed using a human-centered artificial intelligence system. They compared images predicted by probability calculation of the trained set of images for effective classification. Simulation analysis shows that the proposed CNN-RTIPF can classify real-time images with improved classification ratio, sensitivity, and error rate. The proposed CNN-RTIPF has been validated based on the optimization parameter for reliability. To improve the algorithm for movement identification and train the system for many other everyday activities, human-centered artificial intelligence-based Web 4.0 will continue to develop. (shrink)

This article puts forward a novel smooth rotated hyperbola model for support vector machine (RHSSVM) for classification. As is well known, the Support vector machine (SVM) is based on Statistical Learning Theory and performs its high precision on data classification. However, the objective function is non-differentiable at the zero point. Therefore the fast algorithms cannot be used to train and test the SVM. To deal with it, the proposed method is based on the approximation property of the hyperbola (...) to its asymptotic lines. Firstly, we describe the development of RHSSVM from the basic linear SVM optimization programming. Then we extend the linear model to non-linear model. We prove the solution of RHSSVM is convergent, unique, and global optimal. We show how RHSSVM can be practically implemented. At last, the theoretical analysis illustrates that compared with other three typical models, the rotated hyperbola model has the least error on approximating the plus function. Meanwhile, computer simulations show that the RHSSVM can reduce the consuming time at most 54.6% and can efficiently handle large scale and high dimensional programming. -/- . (shrink)

Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper proposes methods for different styles of music classification and migration visualization. This method has the advantages of simple structure, mature algorithm, and accurate optimization. It can find better network weights and thresholds so that particles can jump out of the local optimal solutions previously searched and search in a larger space. The global search uses the gradient method to accelerate the optimization and control the real-time (...) generation effect of the music style transfer, thereby improving the learning performance and convergence performance of the entire network, ultimately improving the recognition rate of the entire system, and visualizing the musical perception. This kind of real-time information visualization is an artistic expression form, in which artificial intelligence imitates human synesthesia, and it is also a kind of performance art. Combining traditional music visualization and image style transfer adds specific content expression to music visualization and time sequence expression to image style transfer. This visual effect can help users generate unique and personalized portraits with music; it can also be widely used by artists to express the relationship between music and vision. The simulation results show that the method has better classification performance and has certain practical significance and reference value. (shrink)

The dynamics of the "Etang de Berre", a brackish lagoon situated close to the French Mediterranean sea coast, is strongly disturbed by freshwater inputs coming from an hydroelectric power station. The system dynamics has been described as a sequence of daily typical states from a set of physicochemical variables such as temperature, salinity and dissolved oxygen rates collected over three years by an automatic sampling station. Each daily pattern summarizes the evolution, hour by hour of the physicochemical variables. This article (...) presents results of forecasts of the states of the system subjected to the simultaneous effects of meteorological conditions and freshwater releases. We recall the main step of the classification tree method used to build up the predictive model (Classification and Regression Trees, Breiman et al., 1984) and we propose a transfer procedure in order to test the stability of the model. Results obtained on the Etang de Berre data set allow us to describe and predict the effects of the environmental variables on the system dynamics with a margin of error. The transfer procedure applied after the tree building process gives a maximum gain in prediction accuracy of about 15%. (shrink)

A smooth rotated hyperbola model for support vector machine (SVM) is proposed. The method is based on the approximation property of the hyperbola to its asymptotic lines. The rotated hyperbola model has the least error on approximating the plus function when the angle between the two asymptotic lines is 135 degree. Experimental result shows that compared with other smooth methods, the rotated hyperbola function support vector machine (RHSSVM) reduces the compute time and can efficiently handle large scale and high dimensional (...) programs. (shrink)

John of Jandun, the early 14th-century master of arts, is selected as a representative of Latin Averroism in an attempt to show that conventional classifications of mediaeval thought break down, and to indicate how the term "Averroist" ought to be qualified and elaborated. Advocacy of the existence of a sensus agens to explain the actualization of immaterial sensible forms residing potentially in material objects, and of the existence of a single soul which is not the form of the body but (...) is united with the body only in the actual process of intellection, places John of Jandun in the tradition of Augustinians like Peckham, Bonaventure, and Scotus. Nevertheless such doctrines are developed in the spirit of the Aristotelianism of the faculty of arts. The author appends to the text a note on some bibliographical problems of his subject's writings as well as a listing of his works. Fifty pages of careful notes accompany a lucid text, in which philosophical issues are first stated, then placed in the context of the middle ages, and finally seen with the light given them by John of Jandun.--M. F. (shrink)

We show a number of improvements in the use of Hidden Conditional Random Fields for phone classification on the TIMIT and Switchboard corpora. We first show that the use of regularization effectively prevents overfitting, improving over other methods such as early stopping. We then show that HCRFs are able to make use of non-independent features in phone classification, at least with small numbers of mixture components, while HMMs degrade due to their strong independence assumptions. Finally, we successfully apply (...) Maximum a Posteriori adaptation to HCRFs, decreasing the phone classification error rate in the Switchboard corpus by around 1% – 5% given only small amounts of adaptation data. (shrink)

Brian Garrett has criticized my diagnosis of the paradox of self-consciousness. In reply, I focus on the classification of 'I'-thoughts, and show how the notion of immunity to error through misidentification can be used to characterize 'I'-thoughts, even though an important class of 'I'-thoughts (those whose expression involves what Wittgenstein called the use of 'I' as object) are not themselves immune to error through misidentification. 'I'-thoughts which are susceptible to error through misidentification are dependent upon those which are not. (...) The dependence here has to do with how a thinker understands what would defeat such thoughts. (shrink)

AdaBoost has been successfully applied to a number of classification tasks, seemingly defying problems of overfitting. AdaBoost performs gradient descent in an error function with respect to the margin. This method concentrates on the patterns which are hardest to learn. However, this property of AdaBoost can be disadvantageous for noisy problems. Indeed, theoretical analysis has shown that the margin distribution plays a crucial role in understanding this phenomenon. Loosely speaking, some outliers should be tolerated if this has the benefit (...) of substantially increasing the margin on the remaining points. In this paper, we propose new noise robust boosting methods using the concepts of ν-Support Vector Classification and Arc-GV. These methods allow for the probability of a pre-specified fraction ν of points to lie in the margin area or even on the wrong side of the decision boundary. This algorithms can give a nicely interpretable way of controlling the trade-off between minimizing the training error and capacity. (shrink)

In this paper I defend what I call the argument from epistemic reasons against the moral error theory. I argue that the moral error theory entails that there are no epistemic reasons for belief and that this is bad news for the moral error theory since, if there are no epistemic reasons for belief, no one knows anything. If no one knows anything, then no one knows that there is thought when they are thinking, and no one knows that they (...) do not know everything. And it could not be the case that we do not know that there is thought when we believe that there is thought and that we do not know that we do not know everything. I address several objections to the claim that the moral error theory entails that there are no epistemic reasons for belief. It might seem that arguing against the error theory on the grounds that it entails that no one knows anything is just providing a Moorean argument against the moral error theory. I show that even if my argument against the error theory is indeed a Moorean one, it avoids Streumer's, McPherson's and Olson's objections to previous Moorean arguments against the error theory and is a more powerful argument against the error theory than Moore's argument against external world skepticism is against external world skepticism. (shrink)

According to the error theory, normative judgements are beliefs that ascribe normative properties, even though such properties do not exist. In this paper, I argue that we cannot believe the error theory, and that this means that there is no reason for us to believe this theory. It may be thought that this is a problem for the error theory, but I argue that it is not. Instead, I argue, our inability to believe the error theory undermines many objections that (...) have been made to this theory. (shrink)

In his paper ?The Error in the Error Theory?[this journal, 2008], Stephen Finlay attempts to show that the moral error theorist has not only failed to prove his case, but that the error theory is in fact false. This paper rebuts Finlay's arguments, criticizes his positive theory, and clarifies the error-theoretic position.

Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 (...) images belong to 3 species at a few developing phases. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results: found that CNN-driven lemon classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

This book provides a novel formulation and defence of moral error theory. It also provides a novel solution to the so-called now what question; viz., the question what we should do with our moral thought and talk after moral error theory. The novel formulation of moral error theory uses pragmatic presupposition rather than conceptual entailment to argue that moral judgments carry a non-negotiable commitment to categorical moral reasons. The new answer to the now what question is pragmatic presupposition substitutionism: we (...) should substitute our current moral judgments, which pragmatically presuppose the existence of categorical moral reasons with ‘schmoral’ judgments that pragmatically presuppose the existence of a specific class of prudential reasons. These are prudential reasons that, when we act on them, contribute to the satisfaction of what the author calls ‘the fundamental desire’; namely, the desire to live in a world with mutually beneficial cooperation. (shrink)

There is a parallel between Plato's argument for the forms at 74b7-c5 in the Phaedo and Frege's argument for the claim that proper names express senses. There is also, I claim, an important asymmetry. The asymmetry explains why it is consistent to accept the conclusion of the Phaedo argument without accepting the conclusion of Frege's argument. The Phaedo argument turns on the possibility of a specific kind of mistaken judgement that may be termed "brute error". Frege's argument does not so (...) depend on the possibility of brute error. (shrink)

Scientists represent their world, grouping and organizing phenomena into classes by means of concepts. Philosophers of science have historically been interested in the nature of these concepts, the criteria that inform their application and the nature of the kinds that the concepts individuate. They also have sought to understand whether and how different systems of classification are related and more recently, how investigative practices shape conceptual development and change. Our aim in this paper is to provide a critical overview (...) of some of the key developments in this philosophical literature and identify some interesting issues it raises about the prospects of the so-called “special sciences”, including psychiatry, psychology, and the mind-brain sciences more generally, to discover natural kinds. (shrink)

Moral error theory of the kind defended by J. L. Mackie and Richard Joyce is premised on two claims: (1) that moral judgements essentially presuppose that moral value has absolute authority, and (2) that this presupposition is false, because nothing has absolute authority. This paper accepts (2) but rejects (1). It is argued first that (1) is not the best explanation of the evidence from moral practice, and second that even if it were, the error theory would still be mistaken, (...) because the assumption does not contaminate the meaning or truth-conditions of moral claims. These are determined by the essential application conditions for moral concepts, which are relational rather than absolute. An analogy is drawn between moral judgements and motion judgements. (shrink)

(2013). Experiencing Error: How Journalists Describe What It's Like When the Press Fails. Journal of Mass Media Ethics: Vol. 28, No. 1, pp. 30-41. doi: 10.1080/08900523.2012.746529.

Moral error theories claim that (i) moral utterances express moral beliefs, that (ii) moral beliefs ascribe moral properties, and that (iii) moral properties are not instantiated. Thus, according to these views, there seems to be conclusive evidence against the truth of our ordinary moral beliefs. Furthermore, many error theorists claim that, even if we accepted moral error theory, we could still in principle keep our first-order moral beliefs. This chapter argues that this last claim makes many popular versions of the (...) moral error theory incompatible with the standard philosophical accounts of beliefs. Functionalism, normative theories of beliefs, representationalism, and interpretationalism all entail that being sensitive to thoughts about evidence is a constitutive feature of beliefs. Given that many moral error theorists deny that moral beliefs have this quality, their views are in a direct conflict with the most popular views about the nature of beliefs. (shrink)

Christos Kyriacou has recently proposed charging moral error theorists with intellectual vice. He does this in response to an objection that Ingram makes against the 'moral fixed points view' developed by Cuneo and Shafer-Landau. This brief paper shows that Kyriacou's proposed vice-charge fails to vindicate the moral fixed points view. I argue that any attempt to make an epistemic vice-charge against error theorists will face major obstacles, and that it is highly unlikely that such a charge could receive the evidential (...) support that it would need in order to play the dialectical role that Kyriacou has in mind for it. I conclude that the moral fixed points view remains in serious trouble. (shrink)

This is a comment on Giora Hon's paper on scientific error.

In this paper, we present a new semantic challenge to the moral error theory. Its first component calls upon moral error theorists to deliver a deontic semantics that is consistent with the error-theoretic denial of moral truths by returning the truth-value false to all moral deontic sentences. We call this the ‘consistency challenge’ to the moral error theory. Its second component demands that error theorists explain in which way moral deontic assertions can be seen to differ in meaning despite necessarily (...) sharing the same intension. We call this the ‘triviality challenge’ to the moral error theory. Error theorists can either meet the consistency challenge or the triviality challenge, we argue, but are hard pressed to meet both. (shrink)

We describe PADUA, a protocol designed to support two agents debating a classification by offering arguments based on association rules mined from individual datasets. We motivate the style of argumentation supported by PADUA, and describe the protocol. We discuss the strategies and tactics that can be employed by agents participating in a PADUA dialogue. PADUA is applied to a typical problem in the classification of routine claims for a hypothetical welfare benefit. We particularly address the problems that arise (...) from the extensive number of misclassified examples typically found in such domains, where the high error rate is a widely recognised problem. We give examples of the use of PADUA in this domain, and explore in particular the effect of intermediate predicates. We have also done a large scale evaluation designed to test the effectiveness of using PADUA to detect misclassified examples, and to provide a comparison with other classification systems. (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

We contend that it is possible to argue reasonably for and against arguments from classifications and definitions, provided they are seen as defeasible (subject to exceptions and critical questioning). Arguments from classification of the most common sorts are shown to be based on defeasible reasoning of various kinds represented by patterns of logical reasoning called defeasible argumentation schemes. We show how such schemes can be identified with heuristics, or short-cut solutions to a problem. We examine a variety of arguments (...) of this sort, including argument from abductive classification, argument from causal classification, argument from analogy-based classification and arguments from classification based on generalizations. (shrink)

How Classification Works attempts to bridge the gap between philosophy and the social sciences using as a focus some of the work of Nelson Goodman. Throughout his long career Goodman has addressed the question: are some ways of conceptualizing more natural than others? This book looks at the rightness of categories, assessing Goodman's role in modern philosophy and explaining some of his ideas on the relation between aesthetics and cognitive theory. Two papers by Nelson Goodman are included in the (...) collection and there are analyses of his work by seven leading academics in anthropology, philosophy, sociology and musicology. (shrink)

In one of the closing paragraphs of Treatise Book 1, Hume provocatively concludes: ‘Generally speaking, the errors in religion are dangerous; those in philosophy only ridiculous’ . Unlike the first clause, the meaning of the second clause is far from obvious. I claim that errors in philosophy are ‘only ridiculous’ for Hume in the sense that – unlike errors in religion – they fail to disturb us psychologically or in practical life. The interesting question, however, is why (...) they fail to disturb us. I suggest that it is their critical role in resolving the psychological instability brought on by philosophical reflection that makes errors in philosophy quite helpful to us and necessary for re-stabilising ourselves. In recognising a positive role for philosophical errors, my account challenges the standard interpretation of Hume's claim according to which ‘ridiculous’ philosophical errors play the merely negative role of being innocuous or safely dismissed. (shrink)

Previously published: Paris: Ancienne librairie Germer Bailliaere, 1901.

Jonas Olson presents a critical survey of moral error theory, the view that there are no moral facts and so all moral claims are false. Part I explores the historical context of the debate; Part II assesses J. L. Mackie's famous arguments; Part III defends error theory against challenges and considers its implications for our moral thinking.

Many philosophers have claimed that normative error theorists are committed to the claim ‘Error theory is true, but I have no reason to believe it’, which to some appears paradoxical. Case (2019) has claimed that the normative error theorist cannot avoid this paradox. In this paper, we argue that there is no paradox in the first place, that is once we clear up the ambiguity of the word ‘reason’, both on the error theorist’s side and those that claim that there (...) is a self-defeat problem. Upon clarification, we also raise scepticism to what exactly the nature of self-defeat is meant to be. (shrink)

ABSTRACT This essay examines error and both external freedom and internal freedom. There is no external freedom (the latitude to choose) without internal freedom (the capacity to choose). Concerning external freedom, it suggests that errors serve as a derivative basis for natural rights. Concerning internal freedom, it overviews four groundbreaking papers from the 1990s by Stephen Boydstun, who suggested that there is no external freedom without internal indeterminism—specifically that associated with quantum probabilities related to neuronal control processes. Also reviewed (...) is work by Elio Conte and by Andrei Khrennikov. Experiments involving a quantum-like model of cognition are discussed. (shrink)