activity
20112022
most citedPredicting college basketball match outcomes using machine learning techniques: some results and lessons learned

21 citations · 41 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2022

Exploiting complex pattern features for interactive pattern mining

Arnold Hien, Samir Loudni, Noureddine Aribi +2

Recent years have seen a shift from a pattern mining process that has users define constraints before-hand, and sift through the results afterwards, to an interactive one. This new…

stat.AP2017

Wages of wins: could an amateur make money from match outcome predictions?

Albrecht Zimmermann

Evaluating the accuracies of models for match outcome predictions is nice and well but in the end the real proof is in the money to be made by betting. To evaluate the question whe…

stat.AP2015

Exploring chance in NCAA basketball

Albrecht Zimmermann

There seems to be an upper limit to predicting the outcome of matches in (semi-)professional sports. Recent work has proposed that this is due to chance and attempts have been made…

cs.CE2015

Exploring the efficacy of molecular fragments of different complexity in computational SAR modeling

Albrecht Zimmermann, Björn Bringmann, Luc De Raedt

An important first step in computational SAR modeling is to transform the compounds into a representation that can be processed by predictive modeling techniques. This is typically…

cs.LG2014★ 2 cited

A feature construction framework based on outlier detection and discriminative pattern mining

Albrecht Zimmermann

No matter the expressive power and sophistication of supervised learning algorithms, their effectiveness is restricted by the features describing the data. This is not a new insigh…

cs.LG2013★ 21 cited

Predicting college basketball match outcomes using machine learning techniques: some results and lessons learned

Albrecht Zimmermann, Sruthi Moorthy, Zifan Shi

Most existing work on predicting NCAAB matches has been developed in a statistical context. Trusting the capabilities of ML techniques, particularly classification learners, to unc…

cs.AI2011★ 18 cited

Pattern-Based Classification: A Unifying Perspective

Björn Bringmann, Siegfried Nijssen, Albrecht Zimmermann

The use of patterns in predictive models is a topic that has received a lot of attention in recent years. Pattern mining can help to obtain models for structured domains, such as g…