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ML-Enhanced Tinychat & Ad Blocker

Ad blocker with machine learning capabilities for Tinychat

如何安裝

您需要先安裝使用者腳本管理器擴展，如 Tampermonkey、Greasemonkey 或 Violentmonkey 之後才能安裝該腳本。

You will need to install an extension such as Tampermonkey to install this script.

您需要先安裝使用者腳本管理器擴充功能，如 Tampermonkey或 Violentmonkey 後才能安裝該腳本。

您需要先安裝使用者腳本管理器擴充功能，如 Tampermonkey或 Userscripts 後才能安裝該腳本。

你需要先安裝一款使用者腳本管理器擴展，比如 Tampermonkey，才能安裝此腳本

您需要先安裝使用者腳本管理器擴充功能後才能安裝該腳本。

（我已經安裝了使用者腳本管理器，讓我安裝！）

如何安裝

你需要先安裝一款使用者樣式管理器擴展，比如 Stylus，才能安裝此樣式

你需要先安裝一款使用者樣式管理器擴展，比如 Stylus，才能安裝此樣式

你需要先安裝一款使用者樣式管理器擴展，比如 Stylus，才能安裝此樣式

你需要先安裝一款使用者樣式管理器擴展後才能安裝此樣式

你需要先安裝一款使用者樣式管理器擴展後才能安裝此樣式

你需要先安裝一款使用者樣式管理器擴展後才能安裝此樣式

（我已經安裝了使用者樣式管理器，讓我安裝！）

作者
Bort Mack
今日安裝
0
安裝總數
11
評價
0 0 0
版本
4.0
建立日期
2024-08-26
更新日期
2024-08-26
尺寸
6.1 KB
授權條款
Bort Mack
腳本執行於

ML-Enhanced Tinychat & PalTalk Ad Blocker

Description:

This advanced userscript provides an adaptive ad-blocking solution for Tinychat, utilizing machine learning techniques to identify and remove ads while maintaining site functionality.

Key Features:

  • Employs machine learning to adaptively identify new ad patterns
  • Learns from user feedback to improve ad detection over time
  • Blocks both visual ads and ad-related network requests
  • Preserves essential site functionality
  • Persists learned patterns between sessions

Usage:

  1. Install a userscript manager like Tampermonkey or Greasemonkey
  2. Install this script from GreasyFork
  3. Visit Tinychat to enjoy adaptive ad blocking
  4. To report a missed ad, use: window.reportMissedAd(element)
  5. To report a false positive, use: window.reportFalsePositive(element)

Note: This script uses machine learning to improve over time. Initial performance may vary, but it will become more accurate with use and feedback.

Changelog:

  • Version 4.0 (2024-08-26)
    • Implemented machine learning algorithm for adaptive ad detection
    • Added user feedback mechanism for reporting missed ads and false positives
    • Introduced feature discovery to learn new ad patterns
    • Implemented persistent storage of learned features and weights
    • Optimized performance with selective feature management

Your feedback and reports help improve this script for everyone. Please use the feedback section below for bug reports, feature requests, or general comments.