{"push_id":694518903,"size":4,"distinct_size":4,"ref":"refs/heads/master","head":"56397067bc3f704292221691fb5643d81bf64918","before":"95168aaf0e5bcc702789f07ce1fc842b86a83a7d","commits":[{"sha":"33f0d8be721bb0e084ff35eb23a7ac77e075d9d6","author":{"email":"0e96acdd59d81fa30ecff9ab5d0669c19aa7852f@users.noreply.github.com","name":"milsen"},"message":"Start 7-3","distinct":true,"url":"https://api.github.com/repos/ea5az/machinelearninggroup31/commits/33f0d8be721bb0e084ff35eb23a7ac77e075d9d6"},{"sha":"ddf65e205159b67ec5416300f455f95baa03f120","author":{"email":"0e96acdd59d81fa30ecff9ab5d0669c19aa7852f@users.noreply.github.com","name":"milsen"},"message":"Improve 7-3, it works\n\nBut I have no idea why.\nThe weights and bias converge, that's a good thing. Even all the errors\ngo to 0. When I used a threshold of 0.5 and a normal plot for the\ndecision boundary, however, it always looked off.\nSetting the threshold to 0.25 and negating the bias in the plot of the\ndecision boundary leads to a correct categorization. But is this the\nproper way of doing it or this indirect hard coding of the solution?","distinct":true,"url":"https://api.github.com/repos/ea5az/machinelearninggroup31/commits/ddf65e205159b67ec5416300f455f95baa03f120"},{"sha":"a30efda47ed0c80ed5cc0522bf81a678f8beaa81","author":{"email":"0e96acdd59d81fa30ecff9ab5d0669c19aa7852f@users.noreply.github.com","name":"milsen"},"message":"Merge branch 'master' of https://github.com/ea5az/machinelearninggroup31","distinct":true,"url":"https://api.github.com/repos/ea5az/machinelearninggroup31/commits/a30efda47ed0c80ed5cc0522bf81a678f8beaa81"},{"sha":"56397067bc3f704292221691fb5643d81bf64918","author":{"email":"0e96acdd59d81fa30ecff9ab5d0669c19aa7852f@users.noreply.github.com","name":"milsen"},"message":"Finish 7-3\n\nAdd classification for test data.\nConvergence is still nice and the pictures look fine, but dubious\nthreshold and negated bias are still there (see previous commit).","distinct":true,"url":"https://api.github.com/repos/ea5az/machinelearninggroup31/commits/56397067bc3f704292221691fb5643d81bf64918"}]}