statistical and machine learning techniques
Tài liệu Báo cáo khoa học: "Extracting Comparative Sentences from Korean Text Documents Using Comparative Lexical Patterns and Machine Learning Techniques" doc
... tences from the Candidates Sen- To effectively eliminate non-comparative sentences from comparative sentence candidates with a CKL2 keyword, we employ machine learning techniques (MEM and Naïve Bayes) ... recall Conclusions and Future Work In this paper, we have presented how to extract comparative sentences from Korean text documents by keyword searching process and machine learning techniques Our ... conducted some experiments by machine learning techniques with all the unigrams of total actual words as baseline systems; they not use any CKs The precision, recall and F1-score of the baseline...
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Báo cáo khoa học: Metabolomics, modelling and machine learning in systems biology – towards an understanding of the languages of cells potx
... and machine learning systems 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 886 D B Kell proling data using machine learning Plant Physiol 126, 943951 Kell DB (2002) Metabolomics and machine ... [38,44]) Figure 2C, D and E highlight the basic and iterative relations between computational models and reality on one hand and between changes in the model that are invoked and its subsequent ... modelling and machine learning systems 50 Cohn DA, Ghabhramani Z & Jordan MI (1996) Active learning with statistical models J Artif Intell Res 4, 129145 51 Hasenjager M & Ritter H (1998) Active learning...
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Báo cáo khoa học: "Using Emoticons to reduce Dependency in Machine Learning Techniques for Sentiment Classification" pot
... classifier are statistically significantly better than those from another, at a confidence interval of at least 95% 2.2 Topic Dependency Engstr¨ m (2004) demonstrated how machineo learning techniques ... corpus of 716 negative and 2,669 positive reviews To create the Polarity 20042 dataset we randomly selected 700 negative reviews and 700 positive reviews, matching the size and distribution of the ... forums, and further newsgroup data from Usenet and Google Groups5 Future work will utilise these sources to collect more examples of emoticon use and analyse any improvement in coverage and accuracy...
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Báo cáo khoa học: "Using Machine Learning Techniques to Build a Comma Checker for Basque" pdf
... Related work Machine learning techniques have been applied in many fields and for many purposes, but we have found only one reference in the literature related to the use of machine learning techniques ... also use machine learning techniques in similar problems such as clause splitting (Tjong Kim Sang E.F and Déjean H., 2001) or detection of chunks (Tjong Kim Sang E.F and Buchholz S., 2000) Learning ... book of philosophy, written com pletely by one author And the third one presents Conclusions and future work We have used machine learning techniques for the task of placing commas automatically...
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Báo cáo khoa học: "Using Machine Learning Techniques to Interpret WH-questions" potx
... predicting another target variable Discussion and Future Work We have introduced a predictive model, built by applying supervised machine- learning techniques, which can be used to infer a user’s ... Topic, Focus, Restriction and LIST Our decision trees were built using dprog (Wallace and Patrick, 1993) – a procedure based on the Minimum Message Length principle (Wallace and Boulton, 1968) The ... decision tree (in number of nodes) and its maximum depth, the attribute used for the first split, and the attributes used for the second split Table shows examples and descriptions of the attributes...
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![data mining and machine learning in cybersecurity [electronic resource]](https://media.store123doc.com/images/document/14/y/op/small_hJlflZCPev.jpg)
data mining and machine learning in cybersecurity [electronic resource]
... Chapter 2, we introduce machine- learning paradigms and cybersecurity along with a brief overview of machine- learning formulations and the application of machine- learning methods and data mining/management ... RIPPER (Lee and Stolfo, 2000), EMERALD (Porras and Neumann, 1997), 10 ◾ Data Mining and Machine Learning in Cybersecurity MADAM ID (Lee and Stolfo, 2000), LERAD (Mahoney and Chan, 2002), and MINDS ... and Machine Learning, Springer, Heidelberg, 2006 Jiawei Han and Micheline Kamber, Data Mining Concepts and Techniques, Morgan Kaufmann, San Francisco, CA, 2001 David J Hand, Heikki Mannila, and...
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Báo cáo sinh học: "Genome-wide prediction of discrete traits using bayesian regressions and machine learning" pptx
... be found in Freund and Schaphire [21], Friedman [12] and GonzálezRecio et al [8] Model 4: Random Forest Random Forest can be viewed as a machine learning ensemble algorithm and was first proposed ... Bayesian regressions (TBA and BTL) and two machine- learning algorithms (RF and boosting) were proposed here to analyze discrete traits in a genomewide prediction context Machine- learning performed better ... between Bayesian regressions and machine- learning were found in the simulated scenario with 1000 QTL TBA and L2B were the methods showing poorest accuracy (0.26 ± 0.10 and 0.24 ± 0.04, respectively)...
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Database development and machine learning prediction of pharmaceutical agents
... 375~4.5K Ligand-based VS (machine learning) , extremely large libraries ( ≥1M) Ligand-based VS (machine learning) , large libraries Machine learning - SVM (2)36, 39, 41 2.5M 22~46 0.0009%~ 0.0018% Machine ... scaled descriptor value falls in the range of and 2.4 Statistical learning methods Machine learning classification methods employ computational and statistical methods to construct mathematical ... 34%~ 94% 13%~ 98% 53~94 41, 42 Machine learning – LMNB (1)39, 41 Machine learning – CKD (18)40 13 Chapter Introduction Ligand-based VS (clustering), large libraries Ligand-based VS (structural signatures),...
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Database development and machine learning classification of medicinal chemicals and biomolecules
... engineering and speech and handwriting recognition The widespread use of machine learning is due to its high accuracy, capability of handling complex data, low cost in applying, and fast performance Machine ... introduction of machine learning classification is provided in next section 13 1.4 Machine learning classification of medicinal chemicals and biomolecules as tools in drug discovery Machine learning ... databases and machine learning classification studies a To develop a machine learning approach to solve an important toxicity related issues in early drug discovery process b To develop a machine learning...
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Introduction to machine learning, second edition (adaptive computation and machine learning)
... unsupervised, and reinforcement learning problems The MIT Press Series on Adaptive Computation and Machine Learning seeks to unify the many diverse strands of machine learning research and to foster ... What Is Machine Learning? Examples of Machine Learning Applications 1.2.1 Learning Associations 1.2.2 Classication 1.2.3 Regression 1.2.4 Unsupervised Learning 11 1.2.5 Reinforcement Learning ... Computation and Machine Learning series appears at the back of this book Introduction to Machine Learning Second Edition Ethem Alpaydn The MIT Press Cambridge, Massachusetts London, England â 2010...
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Tài liệu The Creative Training Idea Book- Inspired Tips and Techniques for Engaging and Effective Learning docx
... Inspired Tips and Techniques for Engaging and Effective Learning This Page Intentionally Left Blank The Creative Training Idea Book Inspired Tips and Techniques for Engaging and Effective Learning ... Idea Book Inspired Tips and Techniques for Engaging and Effective Learning Dynamic Brain Research Memory Attentiveness Learning 10 Learning Modalities Enrichment Brainbased Learning Multiple intelligences ... aromas, activity, and music, I strive to tap into various levels of brain activity My purpose in doing so is to induce and expand learning and assist in retention of ideas, information, and concepts...
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Tài liệu Báo cáo khoa học: "Learning with Unlabeled Data for Text Categorization Using Bootstrapping and Feature Projection Techniques" doc
... contexts and the columns to the centroid-contexts In this paper, the number of input contexts of row and column in CSM is limited to 200, considering execution time and memory allocation, and the ... Technique for Handling Noisy Data of Machine- labeled Data We finally obtained labeled data of a documents unit, machine- labeled data Now we can learn text classifiers using them But since the machinelabeled ... Bennett and A Demiriz, 1999, Semi-supervised Support Vector Machines, Advances in Neural Information Processing Systems 11, pp 368-374 E Brill, 1995, Transformation-Based Error-driven Learning and...
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Báo cáo khoa học: "Phrase-based Statistical Language Generation using Graphical Models and Active Learning" potx
... recognition, natural language understanding, dialogue management and text-tospeech synthesis (Rabiner, 1989; He and Young, 2005; Lef` vre, 2006; Thomson and Young, 2010; e Tokuda et al., 2000) ... with a ‘gold standard’ human utterance from our dataset, which they must compare with utterances generated by models trained with and without active learning on a set of 20, 40, 100, and 362 utterances ... As far as the learning method is concerned, a paired t-test shows that models trained on 20 and 40 utterances using active learning significantly outperform models trained using random sampling,...
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Báo cáo khoa học: "Towards a Unified Approach to Memory- and Statistical-Based Machine Translation" pdf
... Christoph Tillmann, and Herman Ney 1999 Improved alignment models for statistical machine translation In Proceedings of the EMNLP and VLC, pages 20–28, University of Maryland, Maryland S Sato 1992 ... both TMEM and gloss seeds; the translations produced by a greedy decoder that uses only the statistical model and the gloss seed; and translations produced by two commercial systems (A and B) If ... high-standard translation environments in which TMEMs are built manually and constantly checked for quality by specialized teams (Sprung, 2000) Statistical decoding using both a statistical TMEM and...
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Báo cáo khoa học: "Using Machine Learning to Maintain Rule-based Named-Entity Recognition and Classification Systems" pdf
... systems using machine learning (ML) techniques Section presents the two rule-based NERC systems for Greek and French Section explains our method and Section describes the two experiments and presents ... it with two different NERC systems, one for Greek and another one for French The results are very encouraging and show that machine learning techniques can be used for the maintenance of rule-based ... Using Machine Learning Machine learning has been used successfully to control a rule-based system that performs a different task, namely document filtering (Wolinski et al., 2000) The learning...
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machine learning and robot perception bruno apolloni 2012 pot
... models, and how they are used in the core of the landmark learning and recognition system, is described It is followed by introducing how to learn new landmark’s parameters; after that, the landmark ... illumination, distances and view angles to the landmarks Machine learning techniques are being applied with remarkable success to several problems of computer vision and perception [45] Most ... for big public and industrial buildings (factories, stores), and outdoor environments with well-defined landmarks such as streets and roads Fabrication of space-variant sensor and implementation...
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Báo cáo khoa học: "A Machine Learning Approach to Extract Temporal Information from Texts in Swedish and Generate Animated 3D Scenes" docx
... objects and temporal information about events Other meaningful relations and quantities include physical properties such as velocity, color, and shape Time and Event Processing We designed and implemented ... simultaneous, includes, and before, respectively If Sk and Sr represent the set S for the answer key (“Gold Standard”) and system response, respectively, the measures of precision and recall for the ... information in texts, see Setzer and Gaizauskas (2002), inter alia Many of them were incompatible or incomplete and in an effort to reconcile and unify the field, Ingria and Pustejovsky (2002) introduced...
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Learning Techniques for Stock and Commodity Options_1 docx
... the greeks and how they affect the price of an option; probability distributions and how they affect options; option pricing models and their advantages, disadvantages, and foibles and using them ... options from a small overthe-counter backwater of the financial community to a huge and growing market and created a demand for greater information about options pricing The Black-Scholes was deservedly ... has some drawbacks As a result, the model is no longer the standard for options on bonds, foreign exchange, and futures, though the standard models for these three items are modifications of the...
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Learning Techniques for Stock and Commodity Options_2 pdf
... 57 59 Days FIGURE 5.1 Daily Prices Standard statistics can be used to calculate the mean and the standard deviation The standard deviation is simply the statistical description of the variability ... that prices are not random Academic tests of randomness set up straw men and then knock them down On the other hand, there is extensive evidence of seasonality of prices and of implied volatility ... because the current price is known BELL CURVES AND STANDARD DEVIATIONS The standard deviation of prices is a description of the distribution of price changes and a good approximation of actual volatility...
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Learning Techniques for Stock and Commodity Options_3 pptx
... only long 43 shares using this strategy On the other hand, we like the theta and the vega We always like the time decay working in our favor And we have decided that we want to be short options ... positions in theta and vega But let’s take a look at some alternatives What would happen if we closed out the Oct 115 C and sold short the Nov 115 C? We’d sell the Nov at $4.50 and pick up an additional ... Most people just use one or two strategies and never deviate from those However, I recommend keeping an open mind and working harder to gain higher rewards and lower risk by looking at all the options...
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