{"id":30294468,"url":"https://github.com/linkedin/featurefu","last_synced_at":"2025-08-17T01:35:11.337Z","repository":{"id":30800469,"uuid":"34357546","full_name":"linkedin/FeatureFu","owner":"linkedin","description":"Library and tools for advanced feature engineering","archived":false,"fork":false,"pushed_at":"2020-12-16T22:34:16.000Z","size":176,"stargazers_count":564,"open_issues_count":2,"forks_count":109,"subscribers_count":79,"default_branch":"master","last_synced_at":"2024-04-13T23:22:26.089Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/linkedin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-04-21T23:26:41.000Z","updated_at":"2024-04-02T17:40:39.000Z","dependencies_parsed_at":"2022-08-29T06:51:48.748Z","dependency_job_id":null,"html_url":"https://github.com/linkedin/FeatureFu","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/linkedin/FeatureFu","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linkedin%2FFeatureFu","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linkedin%2FFeatureFu/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linkedin%2FFeatureFu/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linkedin%2FFeatureFu/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/linkedin","download_url":"https://codeload.github.com/linkedin/FeatureFu/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/linkedin%2FFeatureFu/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270796216,"owners_count":24647319,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-16T02:00:11.002Z","response_time":91,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-08-17T01:35:07.318Z","updated_at":"2025-08-17T01:35:11.328Z","avatar_url":"https://github.com/linkedin.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"FeatureFu\n======\n\nFeatureFu[l] contains a collection of library/tools for advanced feature engineering, such as using extended s-expression based feature transformation, to derive features on top of other features, or convert a light weighted model (logistical regression or decision tree) into a feature, in an intuitive way without touching any code.\n\nSample use cases:\n\n1. Feature normalization\n\n    \"(min 1 (max (+ (* slope x) intercept) 0))\" : scale feature x with slope and intercept, and normalize to [0,1]\n\n2. Feature combination\n\n   \"(‐ (log2 (+ 5 impressions)) (log2 (+ 1 clicks)))\" : combine #impression and #clicks into a smoothed CTR style feature\n\n3. Nonlinear featurization\n\n   \"(if (\u003e query_doc_matches 0) 0 1)\" : negation of a query/document matching feature\n\n4. Cascading modeling\n\n   \"(sigmoid (+ (+ (..) w1) w0))\"  : convert a logistic regression model into a feature\n\n5. Model combination (e.g. combine decision tree and linear regression)\n\n    \"(+ (* model1_score w1) (* model2_score w2))\" : combine two model scores into one final score\n\nExpr: A super fast and simple evaluator for mathematical s-expressions written in Java.\n\nUsing it is as simple as:\n\n```java\n        VariableRegistry variableRegistry=new VariableRegistry();\n        Expr expression = Expression.parse(\"(sigmoid (+ (* a x) b))\",variableRegistry);\n\n        Variable x = variableRegistry.findVariable(\"x\");\n        Variable a = variableRegistry.findVariable(\"a\");\n        Variable b = variableRegistry.findVariable(\"b\");\n        expression.evaluate();\n\n        Map\u003cString,Double\u003e varMap = new HashMap\u003cString,Double\u003e();\n\n        varMap.put(\"x\",0.2);\n        varMap.put(\"a\",0.6);\n        varMap.put(\"b\",0.8);\n\n        variableRegistry.refresh(varMap);\n        expression.evaluate();\n```\n\n\n## To Build\n  \n  gradle clean build\n\n##Test \n \n \n```java\n\ncd build/expr/lib\n\n$java -cp expr-1.0.jar Expression \"(+ 0.5 (* (/ 15 1000) (ln (- 55 12))))\"\n\n=(0.5+((15.0/1000.0)*ln((55.0-12.0))))\n=0.5564180017354035\ntree\n└── +\n    ├── 0.5\n    └── *\n        ├── /\n        |   ├── 15.0\n        |   └── 1000.0\n        └── ln\n            └── -\n                ├── 55.0\n                └── 12.0\n\n```\n\n## Maven\n\nexpr is available under:\n\n    \u003cdependency\u003e\n      \u003cgroupId\u003ecom.linkedin.featurefu\u003c/groupId\u003e\n      \u003cartifactId\u003eexpr\u003c/artifactId\u003e\n      \u003cversion\u003e0.0.3\u003c/version\u003e\n    \u003c/dependency\u003e\n\n## Gradle\n\n  dependencies {\n    compile \"com.linkedin.featurefu:expr:0.0.3\"\n  }","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinkedin%2Ffeaturefu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flinkedin%2Ffeaturefu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flinkedin%2Ffeaturefu/lists"}