{"push_id":1456834623,"size":6,"distinct_size":0,"ref":"refs/heads/wendy_jenkins","head":"e2a9301ba577ba5a6b4138b4baad4b47970cd34f","before":"d6c1c9574cf788844d832112e9cc0e5440685cd4","commits":[{"sha":"79bd831187f3b09583e0242cf58cb3d9517862c8","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns.  Fixed logical error in checking for column type and allowed loss function for that column.  Added R unit test.\n\nPUBDEV-3728: GLRM logistic loss with binary numeric or categorical column.  Add R unit test.\n\nPUBDEV-3728: binary loss for numeric or categorical column for GLRM.  Added pyunit test.\n\nPUBDEV-3728: logistc loss GLRM.  Simplify GlrmLoss.java to avoid repeated code.\n\nPUBDEV-3728: glrm binary loss.  Found and fix bugs with logistic loss.\n\nPUBDEV-3728: glrm binary loss.  Fixed another bug with reseting array before accumulate sum.\n\nPUBDEV-3728: logistic loss GLRM.  Fixed bug in lgrad calculation for logistic loss.\n\nPUBDEV-3728: glrm binary loss.  Fixed all places where categorical columns with logistic loss are not expanded.\n\nPUBDEV-3728: logistic loss GLRM.  Fixed glrm logistic loss to work with numeric binary columns.\n\nPUBDEV-3728: logistic loss GLRM.  Added check for different user mode in pyunit test.  Added code to prevent user using illegal init mode.\n\nPUBDEV-3728: glrm binary loss.  Minor change to RUnit test.\n\nPUBDEV-3728: logistic loss GLRM.  Fixed bug in looking at wrong loss function lists.\n\nPUBDEV-3728: logistic loss GLRM. Fixed bug in pyunit test.  Referring to non-existence fields.\n\nPUBDEV-3728: glrm binary loss.  Added new method coefNames_glrm to DataInfo.java and leave the original function alone.  Seems like my change has broken other tests.\n\nPUBDEV-3728: logistic loss GLRM. Updated GLRM to call coefNames_glrm method.\n\nPUBDEV-3728: glrm binary loss. Add code to deal with python 3.  Test was failing for python 3.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/79bd831187f3b09583e0242cf58cb3d9517862c8"},{"sha":"7e4e4c021b7b410c8ac776a7b5895d6049d084d3","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns. Fixed typo in GLRM.java.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/7e4e4c021b7b410c8ac776a7b5895d6049d084d3"},{"sha":"979ee11d56f1796652eaf04dd71fe4c3474f1c76","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns.  Incorporated comment from Tomas N from code review.  Thanks, Tomas.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/979ee11d56f1796652eaf04dd71fe4c3474f1c76"},{"sha":"232deb26bf5006fc12fdccd3ee11ae84159bb015","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns. Fixed bug in pyunit unit test found by Megan K.  Thans.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/232deb26bf5006fc12fdccd3ee11ae84159bb015"},{"sha":"dfce4a12de7d1849205e67a41b113c1b12e9a9cc","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns.  Incorporate Pasha code review suggestions.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/dfce4a12de7d1849205e67a41b113c1b12e9a9cc"},{"sha":"e2a9301ba577ba5a6b4138b4baad4b47970cd34f","author":{"name":"wendycwong","email":"4aeb3b58775ceea2e9495f72dfc635135ce94e3d@yahoo.com"},"message":"PUBDEV-3728: GLRM logistic loss for binary categorical or numerical columns.  Incorporate Pasha suggestion to basically treat binary categorical columns with binary loss as numerical columns.  Removed all the hacks I put in from earlier.","distinct":false,"url":"https://api.github.com/repos/h2oai/h2o-3/commits/e2a9301ba577ba5a6b4138b4baad4b47970cd34f"}]}
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