Rule induction

Part 2 book "Essential trig-based physics - Study guide workbook (Vol 2: Electricity and magnetism)" includes content: More resistance equations; logarithms and exponentials, RC circuits; bar magnets; right hand rule for magnetic force; right hand rule for magnetic field; combining the two right hand rules; magnetic force; magnetic field; Ampère’s law; Lenz’s law; Faraday’s law; inductance, AC circuits.

265p dianmotminh03 17-06-2024 1 0   Download

To express the visions forged in the workshops to a wide range of data mining researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes studies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.

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Ebook "Machine learning" includes content: Introduction, concept learning and the general to specific ordering; decision tree learning; artificial neural networks; evaluating hypotheses; bayesian learning; computational learning theory; instance based learning; genetic algorithms; learning sets of rules; analytical learning; combining inductive and analytical learning; reinforcement learning.

421p haojiubujain07 20-09-2023 6 4   Download

Inductive machine learning, and in particular extraction of association rules from data, has been successfully used in multiple application domains, such as market basket analysis, disease prognosis, fraud detection, and protein sequencing. T

7p visteverogers 24-06-2023 6 2   Download

Lecture Data mining: Lesson 10. The main topics covered in this chapter include: classification; classification and regression; classification by decision tree induction; bayesian; classification; other classification methods like rule based, K-NN, SVM, bagging/boosting;... Please refer to the content of document.

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This book "Data mining: Concepts and Techniques (Third edition)" is an extensive and detailed guide to the principal ideas, techniques and technologies of data mining. The book is organised in 13 substantial chapters, each of which is essentially standalone, but with useful references to the book’s coverage of underlying concepts. Please refer to the content of part 2 of book.

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Lecture Calculus - Chapter 10: Computing derivatives. After studying this section will help you understand: we can now apply the mortar to the bricks and start building a collection of known derivatives; let me review a method of proof that is a little subtle and apparently tautological, called the method of induction, better illustrated as the Domino Theory,...

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Survival analysis is an important element of reasoning from data. Applied in a number of fields, it has become particularly useful in medicine to estimate the survival rate of patients on the basis of their condition, examination results, and undergoing treatment.

13p viflorida2711 30-10-2020 13 1   Download

Bài giảng "Học máy - Các phương pháp học có giám sát: Học quy nạp luật - Rule induction" cung cấp cho người học các kiến thức: Phương pháp học quy nạp luật, các bài toán ví dụ, phân loại, chiến lược bao phủ gia tăng, Learn - one - Rule, đánh giá hiệu quản của một luật, các luật logic vị từ,... Mời các bạn cùng tham khảo nội dung chi tiết.

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The induction of alcohol fermentation in roots is a plant adaptive response to flooding stress and oxygen deprivation. Available transcriptomic data suggest that fermentation-related genes are also frequently induced in roots infected with gall forming pathogens, but the biological significance of this induction is unclear.

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This chapter presents the following content: Data mining; business analytics; goal, design, techniques & implementation of data mining; decision trees or rule induction, as a knowledge-modeling tool; predictive techniques; real time decision support.

33p shiwo_ding6 24-05-2019 32 1   Download

Chương 4 - Các phương pháp học có giám sát (Học quy nạp luật - Rule induction). Chương này trình bày những nội dung chính sau: Phương pháp học quy nạp luật, các bài toán ví dụ, phân loại, chiến lược bao phủ gia tăng, Learn - one - Rule, đánh giá hiệu quản của một luật, các luật logic vị từ,... Mời các bạn cùng tham khảo nội dung chi tiết.

30p tieu_vu16 03-01-2019 53 4   Download

The single decision tree gives best results for minority classes, cost metric and global accuracy compared with the bagged boosting of trees of the KDDCup’99 winner and classical decision tree algorithms using the Shannon entropy. In contrast to the complex model of KDDCup winner, our decision tree represents inductive rules (IF-THEN) that facilitate human interpretation.

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Data Mining: Classification and Prediction presents about Classification with decision trees; Artificial Neural Networks; Algorithm for decision tree induction; Attribute Selection Measure; Extracting Classification Rules from Trees .

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This paper presents a method for learning phonological rules from sample pairs of underlying and surface forms, without negative evidence. The learned rules are represented as finite state transducers that accept underlying forms as input and generate surface forms as output. The algorithm for learning them is an extension of the OSTIA algorithm for learning general subsequential finite state transducers. Although OSTIA is capable of learning arbitrary s.-f.s.

7p bunmoc_1 20-04-2013 31 1   Download

This paper demonstrates that generating arguments in natural language requires planning at an abstract level, and that the appropriate abstraction cannot be captured by approaches based solely upon coherence relations. An abstraction based planning system is presented which employs operators motivated by empirical study and rhetorical maxims. These operators include a subset of traditional deductive rules of inference, argumentation theoretic rules of refutation, and inductive reasoning patterns. ...

7p bunrieu_1 18-04-2013 44 3   Download

This paper reports a pilot study, in which Constraint G r a m m a r inspired rules were learnt using the Progol machine-learning system. Rules discarding faulty readings of ambiguously tagged words were learnt for the part of speech tags of the Stockholm-Ume£ Corpus. Several thousand disambiguation rules were induced. When tested on unseen data, 98% of the words retained the correct reading after tagging. However, there were ambiguities pending after tagging, on an average 1.13 tags per word.

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We address the issue of on-line detection of communication problems in spoken dialogue systems. The usefulness is investigated of the sequence of system question types and the word graphs corresponding to the respective user utterances. By applying both ruleinduction and memory-based learning techniques to data obtained with a Dutch train time-table information system, the current paper demonstrates that the aforementioned features indeed lead to a method for problem detection that performs significantly above baseline.

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This work presents a model for learning inference procedures for story comprehension through inductive generalization and reinforcement learning, based on classified examples. The learned inference procedures (or strategies) are represented as of sequences of transformation rules. The approach is compared to three prior systems, and experimental results are presented demonstrating the efficacy of the model.

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This paper compares different measures of graphemic similarity applied to the task of bilingual lexicon induction between a Swiss German dialect and Standard German. The measures have been adapted to this particular language pair by training stochastic transducers with the ExpectationMaximisation algorithm or by using handmade transduction rules. These adaptive metrics show up to 11% F-measure improvement over a static metric like Levenshtein distance.

6p hongvang_1 16-04-2013 43 3   Download