Random Forest Algorithm in Machine Learning
- 2.1
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Brief Introduction
mprove the model Performance using Random Forest.Description
Random Forest Algorithm in Machine Learning:
Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.
Through this training we are going to learn and apply how the random forest algorithm works and several other important things about it.
The course includes the following;
1) Extract the Data to the platform.
2) Apply data Transformation.
3) Bifurcate Data into Training and Testing Data set.
4) Built Random Forest Model on Training Data set.
5) Predict using Testing Data set.
6) Validate the Model Performance.
7) Improve the model Performance using Random Forest.
8) Predict and Validate Performance of Model.
Requirements
- Requirements
- Basic Machine learning concepts and Python.
Data Training Campus
2.1 Raiting
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