MachineLearningLabs

A collection of Machine Learning and Data Mining labs for the ML course taught at INSAT.

During those labs we implemented the :

• Naive Bayes
• KNN
• Random Forests models on the Iris Dataset and used the test validation with different validation metrics using train/test split and Cross Validation

• Principal Component Analysis PCA
• KMeans Clustering
• CAH Agglomerative clustering and Dendrograms
• Silhouette and Elbow to determine the best number of clusters
• Crosstab to validate between models
• We manually implemented DIANA algorithm based on Kmeans

image

• Classifiers Comparison : image image

• Coreelation and dispersion analysis : image
• Elbow :
• image
• Silhouette : image
• Principal Component Analysis : image
• Dendrogram of CAH Agglomerative clustering : image
• Manual DIANA Implementation : image