Knowledge Based Student Performance Prediction Python Projects

Pubblicato il: 30 settembre 2023
sul canale di: PhDDirection

102

Title: - Knowledge Based Student Performance Prediction
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Implementation Plan:
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Step 1: Initially we load a comprehensive real-time dataset including attendance, performance, test scores, and extracurricular activity details.

Step 2: Next, we perform the Preprocessing process, In this process we perform Handling Imbalanced Data, Data Cleaning, and Normalization is applied to the given Dataset.

Step 3: Next, we perform the Feature extraction step, In this step we extract the features such as attendance, previous performance, and standardized test score by using Linear Discriminant Analysis (LDA) Techniques.

Step 4: Next, we perform the Classification process, In this process, We used Logistic Regression (LR) and Support Vector Machines (SVM) techniques to predict student performance, and we built a model to predict student performance using Support Vector Machine using Classification (CLSVM) techniques.

Step 5: The proposed approach is validated using several performance metrics:

5.1: Accuracy
5.2: Precision
5.3: Recall
5.4: F1-score
5.5: Sensitivity
5.6: Specificity
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Software Requirement:
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1. Tool: Python-3.11.4

2. Operating System: Windows 10(64-bit)
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Note:-
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We perform the EXISTING process based on the REFERENCE 5: Title: - Deep knowledge tracking based on attention mechanism for student performance
Prediction.
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