I have classified the species of iris flowers from the famous Iris dataset (https://archive.ics.uci.edu/ml/datasets/iris). The dataset contains measurements for 150 iris flowers from the different species. There are four columns: Sepal Length, Sepal Width, Petal Length, and Petal Width in cm measurement scale. The fifth column represents the Species of the iris flower. I used the following popular machine learning (ML) models here:
- Logistic Regression,
- Support Vector Machine (SVM),
- Decision Tree, and
- K Nearest Neighbors (KNN).
Upon the evaluation, the SVM with the grid search and KNN are expected to be better in classifying the species of the iris data set with higher accuracy among the four ML algorithms used here.
It should be noted that we can also play and compare the performance of the ML models by changing (or including the other dropped) variables and/or by fitting with other ML models.