From efa2ceeb30c03b65a0f871af7cc8a11eb8cf74f5 Mon Sep 17 00:00:00 2001 From: rnhmjoj Date: Tue, 28 Apr 2020 22:16:21 +0200 Subject: [PATCH] readme: add exercise 7 --- README.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/README.md b/README.md index 63aadca..5c4624b 100644 --- a/README.md +++ b/README.md @@ -131,3 +131,22 @@ perform optimally in this case. The `-c` and `-d` options controls whether the convolved or deconvolved histogram counts should be printed to `stdout`. For more options run the program with `-h` to see the usage screen. + + +### Exercise 7 + +`ex-7/bin/main` generates a sample with two classes of 2D points (signal, +noise) and trains either a Fisher linear discriminant or a single perceptron to +classify them (`-m` argument to change mode). Alternatively the weights can be +set manually via the `-w` argument. In either case the program then prints the +classified data in this order: signal then noise. + +To plot the result of the linear classification pipe the output to +`ex-7/plot.py`. The program generates two figures: + - a scatter plot showing the Fisher projection line and the cut line + - two histograms of the projected data and the cut line + +`ex-7/bin/test` takes a model trained in `ex-7/bin/main` and test it against +newly generated datasets (`-i` to set the number of test iterations). The +program prints the statistics of the number of false positives, false +negatives and finally the purity and efficiency of the classification.