Analysis of Ethical Risk Assessment in data driven IT decisions
Performance Analysis of Ethical Risk Assessment & monitoring in data driven IT decisions
Implementation Plan:
Step 1: Initially,we will collect and load data from HR Analytics: Job Change of Data Scientists Dataset.
Step 2: Then, we pre-process the data using Bi-TCN and RNN methods for remove inconsistent records and filtering noisy features
Step 3: Next, we perform a feature selection process using Linear Discriminant Analysis (LDA) for select informative features.
Step 4: Next, we predict the risk using GER-KNN Responsible AI Framework: An Intelligent Model for Ethical Risk Detection in IT Decision Systems based on collected data.
Step 5: Next, we identify and mitigate potential risk factors using the RXAI-chain framework for risk management based on collected data.
Step 6 : Finally, we plot performance for the following metrics:
6.1: Number of Epochs Vs. Accuracy
6.2: Number of Epochs Vs. Precision
6.3: Number of Epochs Vs. Recall
6.4: Number of Epochs Vs. F1-Score
6.5: Number of Epochs Vs. ROC–AUC
Software Requirements:
1. Development Tool: Python 3.11.4 or above
2. Operating System: Windows 10 (64-bit) or above
Dataset:
Link: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists
Note:
1) If the proposed plan does not fully align with your requirements, please provide all necessary details—including steps, parameters, models, and expected outcomes—in advance.
2) Kindly ensure that any missing configurations or specifications are clearly outlined in the plan before confirming.
3) If there’s no built-in solution for what the project needs, we can always turn to reference models, customize our own, different math models or write the code ourselves to fulfil the process.
4) If the plan satisfies your requirement, Please confirm with us.
5) Project based on Simulation only.
We perform with an Existing Approach Ref 3: Title:- Predicting Employee Attrition Using Machine Learning Approaches
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