GitHub PushEvent at 2014-01-24 01:14:38
Repository: h2o
Actor: tomasnykodym
Payload: {"shas":[["e3f66400087995f2d9539552829793a1fe2ce246","dc0f324bbabf67d4738092d0f07f19d30df561f7@gmail.com","Generates comments including column name for each model col domain.","mmalohlava",false],["c2f1bff06d440010b5eab8ce28f7ae57c06778e3","dc0f324bbabf67d4738092d0f07f19d30df561f7@gmail.com","Fix in tests for javaprediction.\n\n- incorrect handling of header (header was not properly skipped)\n- incorrect handling of NAs\n- minor code polishment","mmalohlava",false],["d9c7a4f68887b94a0b7231c0d6b51c7da579c831","dc0f324bbabf67d4738092d0f07f19d30df561f7@gmail.com","Proper handling of NaN in scoring.\n\nNow generated code and interpreter match during handling NaN during\nprediction.","mmalohlava",false],["efd04e939d28f3d72c1e40047bff873f98dd8c87","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Replace the defunct single VM test_NN_sigmoids test with a working\ntest_NN_mnist test.  Checks the validation error after training a ReLU+Dropout\nmodel, for both single-threaded and multi-threaded modes. This is now a true\nregression test (for this set of parameters), in addition to the existing Iris\ntest that confirms that Tanh and Relu (both without Dropout) are giving correct\nresults.\n\nTODO: Add variation of parameters (with ground truths)","Arno Candel",false],["efb2a5f174fdc45a4619585db6ef65ece3c1e3da","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Cosmetics.","Arno Candel",false],["0702570a84f4ea3ee92651783b92d303d6c1292f","303af98bce8e0799414c4d492e9eff323d2247a8@0xdata.com","Fixed small bug in h2o.kmeans.VA and updated more tests","anqi",false],["59623e1273955d233ea68bf0b9f3c64475cfd6a7","303af98bce8e0799414c4d492e9eff323d2247a8@0xdata.com","Add h2o.downloadCSV function to wget file from H2O","anqi",false],["4567d81e6a04d7aafc6c6690891a9eab5129ef45","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Add test for scoring with the final model via a separate json call to H2O.","Arno Candel",false],["5d08d3a75485583b2fb55d0174abe0b43a11ca84","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","again","Arno Candel",false],["b52beca470b3c82bd06416660c2ee4bd9105aca7","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Make the python multi-JVM NeuralNet Mnist test work again, and similarly to the\nsingle-VM case, test for accuracy in validation set prediction, both via model\nprogress page and via separate scoring call.\n\nFor now, only use the multi-threaded single-node mode, even on 3 JVMs.  This\nmeans that only one JVM actually affects the results,  Due to chunking, this\nwill lead to worse accuracy than if a truly distributed (synchronized) mode was\nused. But at least this test tests that the code will run, until the\n'MapReduce' mode is implemented, and data and weight matrices from all machines\nare taken into account.","Arno Candel",false],["1104b06f81e03ddd941d1b20119a9f09aa432bdf","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Add NN testcase for covtype dataset, for single-VM only for now.","Arno Candel",false],["1f3a7ee818df53ea9a02d89be89c3a5205781f0b","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Re-vamp the NN test for the \"twovalues\" synthetic dataset.","Arno Candel",false],["cb4b6097f55be6a447cd3166350a4ffbaafa7936","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Merge branch 'master' into arno-deeplearning","Arno Candel",false],["a67c3f335334b79e284ade35e5a7bc3e30e641e6","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Increase the relative error tolerance for the NN_mnist test case on multi-VM to\n10%. Note: this is needed because only 1 node contributes (each mode is running\nin multi-threaded single-node mode), and doesn't get to see all the training\ndata. Expect this test to be tightened as soon as the distributed version is\nready.","Arno Candel",false],["67b9b1d5724ef44ba2c4d059fc9c7dc37973e986","dc0f324bbabf67d4738092d0f07f19d30df561f7@gmail.com","Merge branch 'master' of github.com:0xdata/h2o","mmalohlava",false],["b398619a21f50a1fa14b860be7948d45cb5ea67a","dc0f324bbabf67d4738092d0f07f19d30df561f7@gmail.com","Report proper NaN if mapping for a given enum-value is not found.","mmalohlava",false],["e1571ae6bb425d7aaf3ecbd79f62db9fe29273a3","303af98bce8e0799414c4d492e9eff323d2247a8@0xdata.com","Fixed a bug in passing class weights to RF1","anqi",false],["5d56e810a147baae5668bf42a04364bf9571688e","329f27436ec86be242c31f07766a746ac09e1189@gmail.com","Use a local single-VM threaded trainer for Mnist example.","Arno Candel",false],["2305e630e9309afe75d0cc599b0eebf11bc5f3ea","303af98bce8e0799414c4d492e9eff323d2247a8@0xdata.com","Fix for PUB-112. Forgot to subtract 1 to get null degrees of freedom","anqi",false],["b8e56d207d68d4c36d3925bd16f206e5f8d39789","303af98bce8e0799414c4d492e9eff323d2247a8@0xdata.com","Dropped col.names parameter by accident","anqi",false]],"size":61,"ref":"refs/heads/va_defaults_renamed","head":"9522d98533522c9eb019fd757c01fc54ccbfbf5d"}