Machine Learning Botnet Detection

Using supervised machine learning algorithm to detect botnet traffic (classify botnet and normal traffic). The samples are labelled so just need the following:

I need 2 files.

The first file should use the following automated algorithms for feature selection:

CFS
ANOVA
Chi-Squared

The following supervised algorithms should be trained and tested.

Decision Tree.
Random Forest.
Support Vector Machines (SVM).
Bernoulli Naive Bayes.
Ridge Classifier.
Logistic Regression.
Naive Bayes.
K-nearest neighbors (KNN).

The second file will allow me to select the features I want manually. The same algorithms should be used for training and testing.

I then want both the results analysis to understand the difference in detection accuracy and they performed.

For each file. I need the following:
Heat map to show which feature correlations.
Confusion matrix for each of the algorithms tested.
ROC curves
Validation curve
Other analyses measurements as necessary.