This page was built in support of our paper "Towards Time Series Classification without
Human Preprocessing" by Patrick Schäfer.
The paper is completely self-contained, the purpose of this webpage is to provide the shotgun distance code, the python-codes and the raw data to readers of the paper.
The spreadsheet which shows the test and train accuracies of each classifiers. This data was used to create Table VI and all scatter plots. It additionally contains the test and train accuracy for all UCR time series datasets and the optimal parameters (mean norming and window size) of the shotgun classifier.
The python code to train and test the SVM classifier.
The python code to train and test the random forest.
Here is the source code for the shotgun distance classificator. The file is password protected. Please email the author to obtain the password.