Project Artificial Intelligence & Machine Learning : Mask Classifier
This project aims to develop a Machine Learning Classifier able to detect the mask in any image of face.
The Pipeline of the model is very simple:
- normalization: MinMaxScaler(feature_range=(0,1));
- pca: PCA(n_components=0.99);
- model: SVC(probability=True).
For training the model it has been chosen a train-test-split, with test size of 0.20 of the total number of sample (50K with mask, 50K no mask).
The choice of the model was selected by comparing 5 differents models on 5folds-CV of the training set. The models compared are:
-GradientBoost: GradientBoostingClassifier() with n_estimators=50;
-RandomForest: RandomForestClassifier() with n_estimators=100;
-NaiveBayes: GaussianNB();
-Logistic: LogisticRegression();
-SVC: SVC(probability=True).
As one can deduce the SVC achieved the best outcome.
To test the model, run* main.py program on your PC.
*If you have Python version 3.10 you should run as follows
exec(open('main.py').read())
my contact: *[email protected]
I'm a Data Analyst, very passionate to the amazing world of Data. Contact me if you want to share a challenge with me! It would be a great chance for me to discover something new.