ExpiredMachine learning with R (RF, Adabost.M1, DT, NB, LR, NN)
FREE
34
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Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)
Requirements
- No Prior programing knowledge is required. However a minimum knowledge of any programming and basic statistics is a plus
Description
- 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
Who this course is for:
- If you are interested on predictive analytic , then this course is a right fit for you.
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