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种子名称： Decision Trees, Random Forests, Bagging & XGBoost R Studio
文件类型： 视频
文件数目： 50个文件
文件大小： 2.43 GB
收录时间： 2021-2-7 11:38
已经下载： 3次
资源热度： 261
最近下载： 2024-6-27 11:12

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Decision Trees, Random Forests, Bagging & XGBoost R Studio.torrent

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/8. Ensemble technique 3 - Boosting/5. XGBoosting in R.mp4186.47MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/3. Machine Learning Basics/1. Introduction, Key concepts and Examples.mp4109.17MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/7. Building a Regression Tree in R.mp4103.33MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/8. Ensemble technique 3 - Boosting/4. AdaBoosting in R.mp4103.01MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/12. Bi-variate Analysis and Variable Transformation.mp4100.45MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/6. EDD in R.mp496.98MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/7. Creating Barplots in R.mp496.72MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/5. Simple Classification Tree/3. Building a classification Tree in R.mp485.11MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/18. Correlation Matrix in R.mp483.17MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/3. Packages in R.mp482.9MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/9. Pruning a Tree in R.mp482.08MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/17. Correlation Matrix and cause-effect relationship.mp471.62MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/3. The Data and the Data Dictionary.mp469.36MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/8. Ensemble technique 3 - Boosting/3. Gradient Boosting in R.mp469.1MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/6. Inputting data part 3 Importing from CSV or Text files.mp460.12MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/6. Ensemble technique 1 - Bagging/2. Bagging in R.mp458.95MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/13. Variable transformation in R.mp455.43MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/16. Dummy variable creation in R.mp443.99MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/6. Splitting Data into Test and Train Set in R.mp443.98MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/2. Understanding a Regression Tree.mp443.73MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/5. Importing the Data set into R.mp443.68MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/1. Basics of Decision Trees.mp442.65MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/8. Creating Histograms in R.mp442.02MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/4. Inputting data part 1 Inbuilt datasets of R.mp440.71MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/3. Machine Learning Basics/2. Steps in building an ML model.mp439.46MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/2. Basics of R and R studio.mp438.84MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/4. The Data set for the Course.mp437.23MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/15. Dummy variable creation Handling qualitative data.mp436.8MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/1. Installing R and R studio.mp435.73MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/8. Ensemble technique 3 - Boosting/1. Boosting techniques.mp434.37MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/5. Simple Classification Tree/1. Classification Trees.mp433.04MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/6. Ensemble technique 1 - Bagging/1. Bagging.mp432.32MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/7. Ensemble technique 2 - Random Forest/2. Random Forest in R.mp430.75MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/8. Outlier Treatment in R.mp430.74MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/10. Missing Value imputation in R.mp426.01MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/2. Setting up R Studio and R Crash Course/5. Inputting data part 2 Manual data entry.mp425.51MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/9. Missing Value imputation.mp424.98MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/7. Outlier Treatment.mp424.5MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/5. Univariate Analysis and EDD.mp424.22MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/1. Gathering Business Knowledge.mp422.29MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/5. Simple Classification Tree/2. The Data set for Classification problem.mp421.97MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/7. Ensemble technique 2 - Random Forest/1. Random Forest technique.mp421.44MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/2. Data Exploration.mp420.52MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/14. Non Usable Variables.mp420.25MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/8. Pruning a tree.mp418.46MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/1. Introduction/1. Welcome to the Course!.mp418.43MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/11. Seasonality in Data.mp417.02MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/4. Simple Decision trees/3. The stopping criteria for controlling tree growth.mp413.96MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/9. Add-on 1 Preprocessing and Preparing Data before making any model/4. Importing the dataset into R.mp413.12MB

[TutsNode.com] - Decision Trees, Random Forests, Bagging & XGBoost R Studio/5. Simple Classification Tree/4. Advantages and Disadvantages of Decision Trees.mp47.76MB