Breadcrumbs Online-Voting-System-using-python / main.pyTop File metadata and controls Code Blame 157 lines (126 loc) · 5.18 KB Raw import tkinter as tk import subprocess import ttkbootstrap as tb from tkinter
Python 3.8+ Django 4.0+ Other dependencies (listed in requirements.txt) Installation Clone the repository: git clone https://github.com/yourusername/online-voting-system.git cd online-voting-system Create and activate a virtual environment (optional but recommended): python -m venv venv # On Wi...
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Community voting system for popular code snippets. Supports embedding of code snippets on other websites. Cons: Limited language support (HTML, CSS, JavaScript). No collaboration feature for real-time code sharing. Pricing: Free 4. WriteCodeOnline WriteCodeOnline has a beautiful UI that is lighter...
By incorporating an interpretability tool, we take our system one step closer to realizing the goals of Responsible AI [18] by focusing on the explainability aspect. LIME focuses on presenting a locally faithful explanation. To do that, it perturbs the instance to be explained, creates a ...
(assuming you expect the private votes to follow the same distribution as the public ones). The second option would be to assign everyone a private one-time key when they vote — a receipt they can look up later. Everyone can then look up the key from their voting receipt on the public...
We chose the XGBoost algorithm to build our answer evaluation system since its performance was the overall best among the four algorithms (see Table 2). Then, the classification results by the XGBoost algorithm were used as the dependent variable, answer quality, in our answer quality formation ...
Your team has been assigned a new task creating a real-time voting system for a new Amazon Prime show, scheduled to occur in four weeks. After the show concludes, a 4-minute voting window will be initiated for tabulating votes. Please evaluate the effectiveness of each action listed below ...
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The majority voting technique is used to combine the final predicted labels. The proposed method achieves an accuracy of 94.0%, 97.0%, and 95.9% to classify CN vs. MCI, CN vs. AD, and MCI vs. AD, respectively. Keywords: diffusion tensor imaging; Alzheimer’s disease; bag of features; ...