The goal is to classify anyone as 'male' or 'female' given just their 'height', 'weight' and 'shoe size' we use scikit-learn package to train first- a decision tree classifier (see: gender-classifier-demo.py) with already existing data set to make it able to predict the gender on it's own given a random set of 'height', 'weight' and 'shoe size Then- we do the same thing but using 4 other classifier models (see:GENDER_CLASSIFIER_USING MULTIPLE MODELS.py) and calculate their accuracy (percentage) using the same data then choose the most accurate model.

*Scikit-learn *numpy *scipy 

*Decision Tree *SVM-SVC *Perceptron *KNeighbors *Naive_bayes-GaussianNB 

python gender-classifier-demo.py python GENDER_CLASSIFIER_USING MULTIPLE MODELS.py 

or use pyCharm