ggjay9/Application-Flow-Identification

Classify applications using flow features with Random Forest and K-Nearest Neighbor classifiers. Explore augmentation techniques like oversampling, SMOTE, BorderlineSMOTE, and ADASYN for better handling of underrepresented classes. Measure classifier effectiveness for different sampling techniques using accuracy, precision, recall, and F1-score.

Language: Jupyter Notebook - Size: 90.6 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

MoinDalvs/Assignment_SVM_Forest_Fire_Prediction

Language: Jupyter Notebook - Size: 5.58 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 3 - Forks: 0

MoinDalvs/Assignment_Decision_Tree_2

Language: Jupyter Notebook - Size: 11.5 MB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 3 - Forks: 0

rohitdwivedula/enzyme-classification

Predict the enzyme class of a given FASTA sequence using deep learning methods including CNNs, LSTM, BiLSTM, GRU, and attention models along with a host of other ML methods.

Language: Python - Size: 76.8 MB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 7 - Forks: 1

iliodipietro/Wine_Quality_Prediction

thesis for Mathematics in Machine Learning course at @Politecnico di Torino.

Language: Jupyter Notebook - Size: 11 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 1