Machine Learning

Brief description of each of the machine learning models are using, the ones we developed and scrapped, and their scores.

Our Model - CatBoost:

Model Accuracy:

Score

The Process:

Inital Outlook

Initial Model

Initial Score

Cross Validation

Cross Validation

CV Chart

CV Scores

Grid Search

Grid Chart

Grid Params

Final Result

Best Code

Best Chart

Verbose

Best Iteration

Best Features

Previous Attempts:

K-Means:

Best Results

KMeans Chart

KMeans Clusters

KMeans Cluster Predicts

Random Forest:

Best Score

Random Forest

Deep Learning:

Best Activation and Results

Deep Learning

Deep Learning Score

Best Optimization and Results

Deep Learning

Deep Learning Score

K Nearest Neighbor (KNN):

KNN Scoring

KNN Chart

Best Score

KNN Best

AutoML:

Classification Models

Classification

Pipeline

Pipeline Code

Pipeline

XGBoost:

Classifier

Classification