Calories Burnt Prediction using Machine Learning Algorithm

Machine learning algorithm used Random Forest Regressor

Random Forest Regressor

• Takes 7 input values i.e. Gender,Age,Height,Weight,Duration,Heart Rate,Body Temprature.

• Machine Learning algorithm used for regression task.

• A random forest is a meta estimator that fits a number of classifying decision trees on various sub-samples of the dataset and uses averaging to improve the predictive accuracy and control over-fitting.

• n_estimators = 10 used.

• used pickle to dump the model for creating a .pkl file to be read by flask web application.

• used flask web framework for deploying the model locally.

• created a Landing page using frontend technologies HTML forms and for designing CSS.

• used HTML forms to take user input.

• after entering details in forms submit button routes the predict METHOD in the app.py i.e. flask web application

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Landing Page

One Hot Encoding

• One-hot Encoding is a type of vector representation in which all of the elements in a vector are 0, except for one, which has 1 as its value, where 1 represents a boolean specifying a category of the element.

Understand One hot encoding

• used 0:Male (0 for male) 1:Female (1 for female)

Before	After
Female	1
Male	0

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Before Prediction

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After Prediction