[Project Addition]:Emotion Classifier

[manishh12]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Emotion Classifier
:red_circle: Aim : Its aim is to classify the emotion into different classes based on the comments in dataset.
:red_circle: Dataset : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset/data?select=Emotion_classify_Data.csv
:red_circle: Approach : Using Naive Bayes and Random Forest algorithm.

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📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

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:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

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:white_check_mark: To be Mentioned while taking the issue :

• Full name :Manish Kumar Gupta
• GitHub Profile Link : https://github.com/manishh12
• Email ID :manishdid360@gmail.com
• Participant ID (if applicable):manishh12
• Approach for this Project : In this analysis, I will start by visualizing the distribution of target classes (emotions) using a count plot to understand the class balance. Following this, I will preprocess the comments by tokenizing, lemmatizing, and removing stop words and punctuation using spaCy. Subsequently, I will encode the emotion labels into numerical values to prepare for classification tasks. Then, I will divide the dataset into training and testing sets to facilitate model training and evaluation. Afterward, I will transform the text data into numerical features using TF-IDF vectorization for further processing.Then, I will train a Multinomial Naive Bayes classifier and assess its performance using accuracy metrics and a comprehensive classification report. Additionally, I will conduct grid search to determine the optimal value for the hyperparameter alpha in the Naive Bayes model. Finally, I will train a Random Forest classifier on the bag-of-words representation of the text data and evaluate its performance using accuracy and a detailed classification report.
• What is your participant role? (Mention the Open Source program)Contributor in GSSOC'24

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Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[abhisheks008]

One issue at a time.

[yashuu02]

Deep Learning Simplified Repository (Proposing new issue) 🔴 Project Title : Emotion Classifier

🔴 Aim : Its aim is to classify the emotion into different classes based on the comments in dataset.

🔴 Dataset : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset/data?select=Emotion_classify_Data.csv

🔴 Approach : Using Naive Bayes ,Random Forest algorithm,SVM,Logistic Regression,LSTM,CNN

[abhisheks008]

Hi @manishh12 can I assign this issue to others as you have raised a lot of open issues, as a result all the contributors want to contribute here looking for open projects.

[manishh12]

Hi @manishh12 can I assign this issue to others as you have raised a lot of open issues, as a result all the contributors want to contribute here looking for open projects.

@abhisheks008 Sure, feel free to assign the appropriate person.

[abhisheks008]

Deep Learning Simplified Repository (Proposing new issue) 🔴 Project Title : Emotion Classifier

🔴 Aim : Its aim is to classify the emotion into different classes based on the comments in dataset.

🔴 Dataset : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset/data?select=Emotion_classify_Data.csv

🔴 Approach : Using Naive Bayes ,Random Forest algorithm,SVM,Logistic Regression,LSTM,CNN

Hi @yashuu02 can you upgrade your approach and make this DL friendly.

[yashuu02]

Yes I can uograde the approach

On Tue, 21 May, 2024, 9:47 pm Abhishek Sharma, @.***> wrote:

Deep Learning Simplified Repository (Proposing new issue) 🔴 Project Title : Emotion Classifier

🔴 Aim : Its aim is to classify the emotion into different classes based on the comments in dataset.

🔴 Dataset : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset/data?select=Emotion_classify_Data.csv

🔴 Approach : Using Naive Bayes ,Random Forest algorithm,SVM,Logistic Regression,LSTM,CNN

Hi @yashuu02 https://github.com/yashuu02 can you upgrade your approach and make this DL friendly.

— Reply to this email directly, view it on GitHub https://github.com/abhisheks008/DL-Simplified/issues/605#issuecomment-2122986125, or unsubscribe https://github.com/notifications/unsubscribe-auth/A6F2FUECN6DDAOKSQSGKIILZDNXTJAVCNFSM6AAAAABH6SO43KVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCMRSHE4DMMJSGU . You are receiving this because you were mentioned.Message ID: @.***>

[abhisheks008]

Yes I can uograde the approach … On Tue, 21 May, 2024, 9:47 pm Abhishek Sharma, @.> wrote: Deep Learning Simplified Repository (Proposing new issue) 🔴 Project Title : Emotion Classifier 🔴 Aim : Its aim is to classify the emotion into different classes based on the comments in dataset. 🔴 Dataset : https://www.kaggle.com/datasets/abdallahwagih/emotion-dataset/data?select=Emotion_classify_Data.csv 🔴 Approach : Using Naive Bayes ,Random Forest algorithm,SVM,Logistic Regression,LSTM,CNN Hi @yashuu02 https://github.com/yashuu02 can you upgrade your approach and make this DL friendly. — Reply to this email directly, view it on GitHub <#605 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/A6F2FUECN6DDAOKSQSGKIILZDNXTJAVCNFSM6AAAAABH6SO43KVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCMRSHE4DMMJSGU . You are receiving this because you were mentioned.Message ID: @.>

Please share your upgraded approach for solving this issue.

[aryanchauh]

I'm girls summer of script contributer . Can your assign me this problem @abhisheks008

[utsabsamadder]

@abhisheks008 I could upgrade the dataset. Instead of doing this with text data I can do it with Human Faces and Detect their Emotion with YOLOv8. I think that might be a bit more unique.

[manishh12]

@abhisheks008 May I kindly request to be assigned this task? I intend to utilize three models: ANN, CNN, and RNN, to conduct a comparative analysis of their respective results.

[abhisheks008]

Hi @manishh12 your approach looks better than others. Assigned this issue to you.

[github-actions[bot]]

Hello @manishh12! Your issue #605 has been closed. Thank you for your contribution!