irhdab/TransLSTM-Predictor
50
A quantitative trading model that combines CNN, Bi-LSTM, and Transformer architectures to achieve state-of-the-art (SOTA) accuracy in stock movement forecasting.
What's novel
A quantitative trading model that combines CNN, Bi-LSTM, and Transformer architectures to achieve state-of-the-art (SOTA) accuracy in stock movement forecasting.
Score Breakdown
Innovation
3 (25%)
Craft
50 (35%)
Traction
11 (15%)
Scope
49 (25%)
Signal breakdown
Innovation
Not Fork+1
Code Novelty+0
Unique Niche+1
Concept Novelty+1
Craft
Ci-1
Tests+3
Polish+0
Releases+0
Has License+5
Code Quality+12
Readme Quality+12
Recent Activity+7
Structure Quality+5
Commit Consistency+2
Has Dependency Mgmt+5
Traction
Forks+0
Stars+6
Hn Points+0
Watchers+0
Early Traction+5
Devto Reactions+0
Community Contribs+0
Scope
Commits+5
Languages+3
Subsystems+5
Bloat Penalty+0
Completeness+7
Contributors+5
Authored Files+8
Readme Code Match+3
Architecture Depth+5
Implementation Depth+8
Evidence
Commits
11
Contributors
1
Files
26
Active weeks
3
TestsCI/CDREADMELicenseContributing
Repository
Language
Python
Stars
3
Forks
0
License
MIT