"hypermetrope yes"

Key Phrases: Naive Bayes, Peter Peggy, Pam Ian, Discrete Estimator, Grace Ray, New Zealand, informational loss function, basic covering algorithm, category utility formula, synthetic binary attributes, contact lens data, gender parentl (see more)

Key Phrases: Naive Bayes, Peter Peggy, Pam Ian, Discrete Estimator, Grace Ray, New Zealand, Ross Quinlan, Incorrectly Classified Instances, informational loss function, basic covering algorithm, category utility formula, synthetic binary attributes, contact lens data, gender parentl, subtree raising, hypermetrope yes, myope yes, machine learning schemes, root relative squared error, numeric prediction, false yes rainy, practical data mining, subtree replacement, combining multiple models, discretized attribute, classifiers package, outlook attribute, maximum margin hyperplane, holdout set, tree inducer, decision tree learner, nominal attributes, numeric attributes (see less)

Key Phrases: Naïve Bayes, Name Function, Peter Peggy, Weka Explorer, Pam Ian, Naive Bayes, informational loss function, category utility formula, generic object editor, synthetic binary attributes, multiresponse linear regression, replicated subtree problem (see more)

Key Phrases: Naïve Bayes, Name Function, Peter Peggy, Weka Explorer, Pam Ian, Naive Bayes, Grace Ray, New Zealand, User Classifier, Gender Parentl, Anna Nikki, Ian Pippa, Visualize Open, Weka Classifier Visualize, informational loss function, category utility formula, generic object editor, synthetic binary attributes, multiresponse linear regression, replicated subtree problem, contact lens data, subtree raising, hypermetrope yes, arff file, myope yes, labor negotiations data, practical data mining, false yes rainy, numeric prediction, outlook attribute, kernel perceptron, subtree replacement, machine learning schemes, holdout set, iris dataset, relative squared error, numeric attributes, weighted instances, maximum margin hyperplane (see less)

Key Phrases: Radial Basis Function, Karush Kuhn Tucker, Monte Carlo, Naive Bayesian Classifier, Statistical Learning Theory, Canonical Correlation Analysis, mean row profile, feature space implicitly, margin slack vector, global granulation, propositional rule learning, turnip experiment (see more)

Key Phrases: Radial Basis Function, Karush Kuhn Tucker, Monte Carlo, Naive Bayesian Classifier, Statistical Learning Theory, Canonical Correlation Analysis, Support Vector Machine, Worcester Polytechnic Institute, Joe Iwanski, Real Time Recurrent Learning, United Kingdom, World Wide Web, mean row profile, feature space implicitly, margin slack vector, global granulation, propositional rule learning, turnip experiment, dense pixel displays, scree diagram, geometric margin, visual data exploration, boundary bias, pendulum data, analysis functionalities, turnip yield, maximal margin hyperplane, functional margin, modern data analysis, intelligent data analysis, subtree mutation, imposing stationarity, fuzzy graphs, prior precision, weights wik, recurrence plots, deviance table (see less)

Key Phrases: Solving Problems, Improving Model Quality, Improving the Model, Naïve Bayes, The Basic Methods, Further Techniques, data preprocessing, social network analysis, reformatting data, temporal data types, false yes rainy, constructing rules (see more)

Key Phrases: Solving Problems, Improving Model Quality, Improving the Model, Naïve Bayes, The Basic Methods, Further Techniques, Decision Analysis, Algorithm Adjustment, Simple Examples, Descriptive Data Summarization, Morgan Kaufmann, Child Child, Constructing Decision Trees, Balance Status, Delta Baker Charlie Echo Able, John Wiley, Job Cost Genomes, Statistical Modeling, Modeling Risk Preferences, Complex Systems, World Wide Web Conference, Age Status, Suppose Joe, Absent Leaf, Netezza Corporation, data preprocessing, social network analysis, reformatting data, temporal data types, false yes rainy, constructing rules, crew assignments, covering algorithms, mining association rules, data rollup, smoothed residual variance estimate, input battery variables, anachronistic variables, residual test model, many mining tools, concept hierarchy generation, data warehouse bus, contact lens data, numerosity reduction, attribute subset selection, predictions unsatisfactory, clique attack, multiresponse linear regression, solution terrain, data discretization (see less)