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Building-a-Classification-Model-Python

This project demonstrates how to build a simple machine learning model in Python using the scikit-learn package. The model is a classification model used to classify Iris flowers using the random forest algorithm. The project includes the following steps:

  • importing necessary libraries and modules
  • adding the Iris dataset
  • splitting the dataset into training and testing sets
  • defining the model and its parameters
  • training the model
  • testing the model and evaluating its performance
  • using the trained model to make predictions on new data

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