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Chapter 5: Even more Group Procedure – K-Nearby Locals and you can Help Vector Machines K-nearby locals Service vector servers Organization instance Team skills Investigation skills and preparation Modeling and you will investigations KNN modeling SVM acting

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Table out-of Information Preface Chapter step one: A process to achieve your goals The method Organization wisdom Pinpointing the organization mission Examining the difficulty Determining the newest logical goals Producing a venture bundle Investigation information Studies preparing Acting Research Deployment Algorithm flowchart Conclusion

Section dos: Linear Regression – The fresh new Blocking and you can Tackling from Server Understanding Univariate linear regression Organization facts Multivariate linear regression Business knowledge Studies expertise and you can planning Acting and you may investigations Most other linear model factors Qualitative have Correspondence terminology Bottom line

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Section step 3: Logistic Regression and Discriminant Data Classification tips and you can linear regression Logistic regression Organization wisdom Data skills and you can planning Modeling and you will evaluation

step one 8 9 ten 11 a dozen a dozen twelve thirteen thirteen fourteen fifteen fifteen 16 21 22 23 twenty six thirty-two thirty two 33 thirty-six fifty fifty 52 54 55 56 56 57 58 63

Section cuatro: Advanced Feature Solutions in Linear Habits Regularization basically Ridge regression LASSO Flexible web Organization case Business skills Research insights and you will preparation Modeling and you will testing Most useful subsets Ridge regression LASSO Flexible internet Cross-recognition which have glmnet Model solutions Regularization and group Logistic regression analogy Bottom line

64 67 70 73 76 82 85 86 87 88 88 89 89 89 90 96 96 one hundred 105 108 111 113 114 114 117 118 119 120 124 124 125 131 131 136 139 142 144 145

An introduction to the methods Knowing the regression trees Category trees Arbitrary forest Gradient improving Organization case Modeling and you will testing

Chapter 7: Neural Communities and you may Deep Training Addition in order to neural networking sites Deep studying, a not-so-deep evaluation Strong studying resources and advanced methods Team skills Research understanding and you can planning Modeling and you may testing An example of deep learning Liquid records Studies upload to help you H2o Create train and you will attempt datasets Modeling Conclusion

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Hierarchical clustering Range data K-function clustering Gower and you can partitioning up to medoids Gower PAM Random tree Company facts Research expertise and you will preparation Modeling and testing

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