Читать книгу Machine Learning Techniques and Analytics for Cloud Security - Группа авторов - Страница 58

Step 1: Read dataset G = {G^N, G^C} and make G = (G^N)^T∪(G^C)^T.

Step 2: Partition dataset into training and test dataset with a ratio.

Step 3: Standardize the dataset’s value onto unit scale.

Step 4: Repeat steps 5 to 9 till all genes are selected and processed.

Step 5: Selecting r genes at random and mark them.

Step 6: Applying PCA on selected genes to retain α% of the variance.

Step 7: Training the selected gene on Logistic Regression model.

Step 8: Predicting accuracy score by comparing the test data and predicted data

Step 9: If accuracy_score>threshold_value, then store these genes in a new list as resultant set of gene.

[end if]

Step 9: Stop