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I have analysed the iris dataset by using coorelation matrix, scatterplots finding the key insights in the data and then trained the dataset with 3 algorithms finally reaching the 100% accuracy.

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Irisdataset_classification

Dataset Information

The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.

Attribute Information:-

  • sepal length in cm
  • sepal width in cm
  • petal length in cm
  • petal width in cm
  • species: -- Iris Setosa -- Iris Versicolour -- Iris Virginica

Libraries used-

  • pandas
  • matplotlib
  • seaborn
  • scikit-learn

Algorithms

  • Logistic Regression
  • K-Nearest Neighbors
  • Decision Tree

    • Best Model Accuracy: 100.00

    About

    I have analysed the iris dataset by using coorelation matrix, scatterplots finding the key insights in the data and then trained the dataset with 3 algorithms finally reaching the 100% accuracy.

    Topics

    python data-science machine-learning logistic-regression kmeans decision-trees

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