Predict species of iris flower using various ML classifiers

[ShashankP19]

Description

Given the dataset on iris flowers, predict the species of flower given the following features :

1. sepal length
2. sepal width
3. petal-length
4. petal-width

There are three species:

1. virginica
2. setosa
3. versicolor

The dataset can be found here

Details

• Technical Specifications: python, scikit-learn, pandas, numpy
• Type of issue: Multiple issues
• Time Limit: 3 days for each classifier implementation

Issue requirements / progress

Train the model on train data. Predict target values using test data. Find accuracy of the model comparing with actual test data targets Note: Each pull request should be a solution using only one model.

• [ ] Using K Neighbors Classifier
• [ ] Using Decision Tree Classifier
• [x] Using Gaussian Naive Bayes
• [x] Using Support Vector Classifier
• [ ] Using Gaussian Process Classifier
• [x] Using Random Forest Classifier
• [x] Using Multi-layer Perceptron (MLP) Classifier
• [ ] Using AdaBoost Classifier
• [ ] Using Quadratic Discriminant Analysis

Resources

• To help you get started, the starter code iris_starter_code.ipynb is present in /machine_learning/iris
• Jupyter notebook installation
• scikit-learn KNeighborsClassifier
• scikit-learn DecisionTreeClassifier
• scikit-learn GaussianNB
• scikit-learn SupportVectorClassifier
• scikit-learn GaussianProcessClassifier
• scikit-learn RandomForestClassifier
• scikit-learn MLPClassifier
• scikit-learn AdaBoostClassifier
• scikit-learn QuadraticDiscriminantAnalysis
• pandas tutorial
• numpy tutorial

Directory Structure

Place your solution file in path as follows.

• For K Neighbors Classifier /machine_learning/iris/knn/<your_solution_file>
• For Decision Tree Classifier /machine_learning/iris/dtc/<your_solution_file>
• For Gaussian Naive Bayes /machine_learning/iris/gnb/<your_solution_file>
• For Support Vector Classifier /machine_learning/iris/svc/<your_solution_file>
• For Using Gaussian Process Classifier /machine_learning/iris/gpc/<your_solution_file>
• For Using Random Forest Classifier /machine_learning/iris/rfc/<your_solution_file>
• For Using Multi-layer Perceptron (MLP) Classifier /machine_learning/iris/mlp/<your_solution_file>
• For Using AdaBoost Classifier /machine_learning/iris/abc/<your_solution_file>
• For Using Quadratic Discriminant Analysis /machine_learning/iris/qda/<your_solution_file>

Note

Please claim the issue first by commenting here before starting to work on it.

[mehnazyunus]

Hi, I'd like to work on Gaussian Naive Bayes Classifier.

[ShashankP19]

Hi @mehnazyunus , you are assigned to work on Gaussian Naive Bayes Classifier. Go ahead.

[shakeelsamsu]

Hi, I'd like to work on the Support Vector Classifier

[GajeshS]

Hi, I would like to work on the MLP Implementation

[bhuvanakundumani]

I would like to work on Random Forest Classifier.

[bhuvanakundumani]

Hi

I would like to work on Decision Tree Calssifier

[ShashankP19]

@bhuvanakundumani You are assigned Decision Tree Classifier. Go ahead.

[bhuvanakundumani]

Ok. Thanks

[bhuvanakundumani]

Hi, Implemented the Decision tree classifier

[Madhuparna04]

Hi ,I would like to work on KNN classifier

[ShashankP19]

@Madhuparna04 KNN classifier has already been taken. Choose some other classifier.