scikit-learn

6 Steps

1. 1

   Install scikit-learn: Install scikit-learn using pip. This command will download and install the latest version of the library along with its dependencies.

2. 2

   Load the Iris dataset: Load the Iris dataset, a classic dataset for classification, using scikit-learn's built-in datasets module.

3. 3

   Split data into training and testing sets: Split the dataset into training and testing sets using `train_test_split`. This allows you to evaluate the performance of your model on unseen data.

4. 4

   Train a Logistic Regression model: Create and train a Logistic Regression model using the training data. Logistic Regression is a linear model used for classification tasks.

5. 5

   Make predictions: Use the trained model to make predictions on the test data.

6. 6

   Evaluate the model: Evaluate the performance of the model using metrics like accuracy. This provides insight into how well the model is generalizing to new data.