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[FreeTutorials Us] [UDEMY] Fundamentals of Decision Trees in Machine Learning [FTU]

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Title: UDEMY Fundamentals of Decision Trees in Machine Learning FTUGroup: NOGRPSource: Udemy
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01 Introduction/001 Welcome.mp414.05 MB
01 Introduction/002 Introduction.mp410.63 MB
01 Introduction/003 Getting started.mp420.82 MB
01 Introduction/attached files/003 Ex-Files-MachineLearning-Trees.zip76.06 KB
02 Decision Trees in IBM SPSS Modeler/004 Decision tree options in SPSS Modeler.mp430.28 MB
02 Decision Trees in IBM SPSS Modeler/005 Building CHAID model and add a second model with CRT.mp464.14 MB
02 Decision Trees in IBM SPSS Modeler/006 Analysis nodes.mp426.75 MB
02 Decision Trees in IBM SPSS Modeler/007 Lift and gains chart.mp438.83 MB
03 CHAID/008 Whats an algorithm.mp417 MB
03 CHAID/009 Chi-squared.mp428.83 MB
03 CHAID/010 Buliding a tree interactively.mp430.21 MB
03 CHAID/011 Bonferonni adjustment and level of measurement.mp464.6 MB
03 CHAID/012 CHAID.mp492.4 MB
04 CRT/013 Gini coefficient.mp421.3 MB
04 CRT/014 Understanding CRT.mp483.97 MB
04 CRT/015 The complete CRT tree.mp426.63 MB
04 CRT/016 Stopping rules in CHAID and CRT.mp447.22 MB
04 CRT/017 Improving your model.mp460.96 MB
05 QUEST/018 Understanding QUEST.mp46.59 MB
05 QUEST/019 How QUEST handles variables.mp472.22 MB
05 QUEST/020 How QUEST handles missing data.mp426.51 MB
05 QUEST/021 Pruning and stopping rules in QUEST.mp444.93 MB
05 QUEST/attached files/018 Ex-Files-ML-Adv-DecisionTrees.zip873.26 KB
06 C5.0/022 ID3 and C4.5.mp416.1 MB
06 C5.0/023 Winnowing attributes and rule sets.mp463.06 MB
06 C5.0/024 Understanding information gain.mp424.86 MB
06 C5.0/025 Pruning in C5.0.mp477.41 MB
06 C5.0/026 How C5.0 handles missing data.mp415.27 MB
07 Advanced Topics/027 Ensembles.mp461.71 MB
07 Advanced Topics/028 Bagging.mp4101.39 MB
07 Advanced Topics/029 Random forests.mp428.09 MB
07 Advanced Topics/030 Boosting.mp441.93 MB
07 Advanced Topics/031 Costs and priors.mp441.65 MB

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