Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)
- 3.3
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3 hours on-demand video
$
9.99
Brief Introduction
RF, Adabost.M1, DecisionTree, Logistic Regression , Naive Bayes, Neural Network, CNN, K-mean , Linear regressDescription
- How to download and install R
- How to set your working directory import your data and detect rows containing missing values
- For binary classification
- Training and prediction using the Random Forest model , prediction accuracy, Confusion matrix and confidence interval
- Training and prediction using the Adabost.M1 model , prediction accuracy, Confusion matrix and confidence interval
- Training and prediction using the Decision Tree model , prediction accuracy, Confusion matrix and confidence interval
- Training and prediction using the logistic regression model, prediction accuracy, confusion matrix and confidence interval
- Training and prediction using the Naive Bayes model, prediction accuracy, confusion matrix and confidence interval
- Training and prediction using the Neural Network model , prediction accuracy, confusion matrix and confidence interval
- Training and prediction using the Convolutional neural network (KNN) , prediction accuracy, confusion matrix and confidence interval
- How to combine models to predict
- Missing values treatment ,variables selection and prediction using a linear regression model
- K mean Clustering
Requirements
- Requirements
- No Prior programing knowledge is required. However a minimum knowledge of any programming and basic statistics is a plus
Modeste Atsague
3.3 Raiting
Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)
- 3.3
-
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RF, Adabost. M1, DecisionTree, Logistic Regression , Naive Bayes, Neural Network, CNN, K-mean , Linear regress...
