Django Club

Iris Classification

Using Support Vector Machine Classification Model

After submitting the form, wait at least 10 seconds for the model to calculate and show the result.
Also, all entered float numbers must have at most 2 decimal points, like: 1.23

Model Description:

Classification is a supervised machine learning method where the model tries to predict the correct label of a given input data. One of the algorithms used for classification is “Support Vector Machine” or abbreviation, SVM.
Here, we use the iris.csv dataset for classification purposes and you can download the dataset from the link on top of this page. This dataset has 4 features:
Sepal Length”, “Sepal Width”, “Petal Length” and “Petal Width
And the label for each item in the dataset is the type of iris flower which has 3 values:
Iris Setosa”, “Iris Versicolor” and “Iris Virginica”.
In the above form, you enter the values of 4 features and the model returns the type of iris flower in a pop-up form. Notice that the range of each feature is as below:
4 < sepal length < 8
2 < sepal width < 5
1 < petal length < 7
0.1 < petal width < 3
The sample code used to train a “svm” classification model, is provided in the link on top of this page. Each time you run this form and classification predictions happen, the values will store in the database, and with the link “result” on top of this page, you will see the previous results of the model prediction. Your recent run will be added to the end of this list.