linyiqun/DataMiningAlgorithm
数据挖掘18大算法实现以及其他相关经典DM算法
- Repository: https://github.com/linyiqun/DataMiningAlgorithm
- Commit:
6f5caa12cae4535d936a9b6d533e18640881966c - Generated: 2026-11-13T23:27:04+00:00
- Scorer 0.1.0, scoring prov-4+qual-2+sec-2, report schema v2
Scores
| Pillar | Score | Signal | Confidence | Coverage |
|---|---|---|---|---|
| AI provenance (estimated AI-generated share) | 0 | none-detected | 63% | 100% |
| Code quality | 42 | poor | 90% | 100% |
| Security | 82 | adequate | 85% | 100% |
AI provenance
No AI attribution or AI-consistent velocity signals detected.
- Explicitly attributed share (lower bound): 0.0%
- Unattributed share in AI-consistent velocity bursts: 0.0%
- Estimated AI-generated share: 0.0%
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2015-01 | 6,749 | 0% |
| 2015-02 | 5,897 | 0% |
| 2015-03 | 3,247 | 0% |
| 2015-04 | 2,030 | 0% |
| 2015-06 | 419 | 0% |
| 2015-07 | 698 | 0% |
| 2015-08 | 295 | 0% |
AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.
Code quality
Code quality is poor: test-to-source ratio 0.00, no CI test run detected; 15% of function code in complex or long functions; 22% duplicated lines. Weakest area: testing.
| Area | Score |
|---|---|
| Complexity (lizard) | 64 |
| Duplication | 27 |
| Code smells (Opengrep) | 96 |
| Tests and CI | 0 |
| Documentation | 40 |
| Type safety | n/a |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 679; mean complexity 3.9, 90th percentile 9; 18 complex and 3 long functions
- Duplicated lines: 21.9% of 12,322 compared
- Tests: 0 test lines for 19,189 source lines (ratio 0.00); CI test commands: none detected; 0% of recent source commits also change tests
- Docs missing or thin: license, contributing, changelog
Most complex functions:
- decision_function::svm_train in StatisticalLearning/DataMining_SVM/libsvm/svm.java: complexity 47, 189 lines
- decision_function::svm_check_parameter in StatisticalLearning/DataMining_SVM/libsvm/svm.java: complexity 40, 92 lines
- SolutionInfo::Solve in StatisticalLearning/DataMining_SVM/libsvm/svm.java: complexity 40, 210 lines
- decision_function::svm_load_model in StatisticalLearning/DataMining_SVM/libsvm/svm.java: complexity 29, 131 lines
- decision_function::svm_cross_validation in StatisticalLearning/DataMining_SVM/libsvm/svm.java: complexity 27, 100 lines
Security
Security posture is adequate: no high-impact findings. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 100 |
| Vulnerable dependencies (OSV) | n/a |
| CI workflows (zizmor) | n/a |
| Posture (policy, updates, signing, lockfiles) | 0 |
| OpenSSF Scorecard | n/a |
- Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits
Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.
Repository profile
- Source lines: 19,189; test lines: 0
| Language | Lines |
|---|---|
| Java | 19,189 |