Improve Accuracy by Exploring Alternative Machine Learning Models

[ayesha-119]

Prerequisites

• [X] I am an Open Source Contributor
• [X] I checked to make sure that this issue has not already been filed

Description

As a participant in the Girls Script Summer of Code (GSSoC) program, I have noticed an opportunity to enhance the accuracy of the machine learning model by exploring alternative models. Although Linear Regression, Logistic Regression, Perceptron, and Decision Tree Classifiers have been applied, I believe that considering additional models can help us achieve higher predictive performance.

To address this, I propose the following steps:

1. Research and Evaluate Alternative Models: Conduct a thorough investigation of various machine learning models suitable for the given task, such as Random Forest, Support Vector Machines (SVM), Gradient Boosting Models (e.g., XGBoost, LightGBM), Neural Networks (e.g., using TensorFlow or PyTorch), Naive Bayes, K-Nearest Neighbors (KNN), and others. Compare their strengths, weaknesses, and suitability for the dataset.

2. Implement and Train Alternative Models: Select a subset of promising models and implement them in the project. Utilize appropriate libraries and frameworks for each model and train them on the Drug Review Dataset, following best practices and considering proper hyperparameter tuning techniques.

3. Performance Evaluation and Comparison: Evaluate the performance of the alternative models using appropriate evaluation metrics (e.g., accuracy, precision, recall, F1-score) and compare them against the existing models. Identify the models that show improved accuracy or other desirable performance characteristics.

4. Fine-tuning and Model Ensemble: If a specific alternative model outperforms the existing ones, consider further fine-tuning its hyperparameters to maximize its potential. Additionally, explore the possibility of creating a model ensemble by combining the strengths of multiple models to achieve even higher accuracy.

5. Documentation and Reporting: Document the findings, including the performance comparison, insights gained, and recommendations for selecting the most accurate model(s). Provide clear instructions on integrating the recommended models into the project and any modifications required for the existing implementation.

Screenshots

No response

Code of Conduct

• [X] I follow Contributing Guidelines of this project.

[ayesha-firdaus]

I would like to work on this issue under GSSOC'23. I would appreciate if the issue is assigned to me.

[UditSharma9999]

I'm a contributor for GSSoC '23, I want to work on this issue. Please assign me.

[sijalalyy]

I am GSSOC 23 contributor assign this to me i want to work on this

[Rakesh9100]

@ayesha-119 Assigning you, Go ahead

[ayesha-119]

Haven't you assigned this issue to me? @Rakesh9100

[Rakesh9100]

@ayesha-119 I have assigned you but it's been 4 days and no update from your side. If you are working pls tell me.

[ayesha-119]

@ayesha-119 I have assigned you but it's been 4 days and no update from your side. If you are working pls tell me.

Yeah I'm

@ayesha-119 I have assigned you but it's been 4 days and no update from your side. If you are working pls tell me.

Yes I'm working on it.

[Rakesh9100]

Okay then what the status? When will you create PR? @ayesha-119

[ayesha-119]

Okay then what the status? When will you create PR? @ayesha-119 tomorrow or the day after that

[Rakesh9100]

Okay

[jahnvisahni31]

Hi, @Rakesh9100 I would like to contribute. Please assign the task to me under GSSOC'23.

[Mimi97-aqua]

I am a GSSOC2023 contributor and would like for this to be assigned to me please.

[Rakesh9100]

@ayesha-firdaus @sijalalyy Would you like to work? If yes describe in brief the work you will do.

[sijalalyy]

Yes, I want to work on this issue. Many alternative ML models like KNN, SVM, Random Tree can be used to improve accuracy.

[Rakesh9100]

Proceed @sijalalyy Assigned

[sijalalyy]

Ok. Thankyou.

[Rakesh9100]

@sijalalyy Update pls

[sijalalyy]

@sijalalyy Update pls

70% done, going to create PR in 2 days, hopefully by wednesday

[sijalalyy]

@Rakesh9100 sorry for the delay because of unexpected electricity and internet issues due to cyclone biparjoy, i will create PR in two days. Thankyou.

[Rakesh9100]

Any Update finally @sijalalyy

[sijalalyy]

yes, i will create PR today

[github-actions[bot]]

👋 @ayesha-119 This issue is closed. Thank You!!