Basic data analysis and visualization techniques are applied on Iris flower dataset. After pre-prcoessing and analysis few of the machine-learning algorithms are applied. The dataset contains different features like:
- Sepal Width
- Sepal Length
- Petal Width
- Petal Length
- Species name
- numpy
- pandas
- matplotlib
- seaborn
- statsmodels
- sklearn
- Logistic Regression
- K-nearest Neighbour
- Decision Tree
- Random Forest
- Gradient Boost
- Support Vector Machine
- Gaussian Naive Bayes
- Neural Networks
Here Iris dataset is analysed with basic data analysis techniques and applied different machine learning algorithms for prediction and classification operation.