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Fundamentals of Decision Trees in Machine Learning
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Fundamentals of Decision Trees in Machine Learning (Size: 1.29 GB) (Files: 41)
Fundamentals of Decision Trees in Machine Learning
07 Advanced Topics
028 Bagging.mp4
027 Ensembles.mp4
029 Random forests.mp4
030 Boosting.mp4
031 Costs and priors.mp4
ReadMe.txt
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ReadMe.txt
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01 Introduction
001 Welcome.mp4
002 Introduction.mp4
003 Getting started.mp4
Must Read.txt
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attached files
003 Ex-Files-MachineLearning-Trees.zip
02 Decision Trees in IBM SPSS Modeler
004 Decision tree options in SPSS Modeler.mp4
005 Building CHAID model and add a second model with CRT.mp4
006 Analysis nodes.mp4
007 Lift and gains chart.mp4
03 CHAID
008 Whats an algorithm.mp4
009 Chi-squared.mp4
010 Buliding a tree interactively.mp4
011 Bonferonni adjustment and level of measurement.mp4
012 CHAID.mp4
04 CRT
013 Gini coefficient.mp4
014 Understanding CRT.mp4
015 The complete CRT tree.mp4
016 Stopping rules in CHAID and CRT.mp4
017 Improving your model.mp4
05 QUEST
018 Understanding QUEST.mp4
019 How QUEST handles variables.mp4
020 How QUEST handles missing data.mp4
021 Pruning and stopping rules in QUEST.mp4
attached files
018 Ex-Files-ML-Adv-DecisionTrees.zip
06 C5.0
022 ID3 and C4.5.mp4
023 Winnowing attributes and rule sets.mp4
024 Understanding information gain.mp4
025 Pruning in C5.0.mp4
026 How C5.0 handles missing data.mp4
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