Unified recurrent network for many feature types

no code implementations • 27 Sep 2018 • Alexander Stec, Diego Klabjan, Jean Utke

We also include two types of static (whole sequence level) features, one related to time and one not, which are combined with the encoder output.

Time Series Time Series Analysis

Unified recurrent neural network for many feature types

no code implementations • 24 Sep 2018 • Alexander Stec, Diego Klabjan, Jean Utke

We also include two types of static (whole sequence level) features, one related to time and one not, which are combined with the encoder output.

Time Series Time Series Analysis

Nested multi-instance classification

no code implementations • 30 Aug 2018 • Alexander Stec, Diego Klabjan, Jean Utke

We also introduce a method to replace instances that are missing which successfully creates neutral input instances and consistently outperforms standard fill-in methods in real world use cases.

Classification General Classification

Forecasting Crime with Deep Learning

no code implementations • 5 Jun 2018 • Alexander Stec, Diego Klabjan

With our best model we are able to predict the correct bin for overall crime count with 75. 6% and 65. 3% accuracy for Chicago and Portland, respectively.

Crime Prediction