[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - The relationship between Precision-Recall and ROC curves

[ACM Press the 23rd international confer

✍ Davis, Jesse; Goadrich, Mark 📂 Article 📅 2006 🏛 ACM Press ⚖ 170 KB

Receiver Operator Characteristic (ROC) curves are commonly used to present results for binary decision problems in machine learning.However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm's performance. We show that a deep conne

[ACM Press the 23rd international confer

[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - Dynamic topic models

✍ Blei, David M.; Lafferty, John D. 📂 Article 📅 2006 🏛 ACM Press ⚖ 406 KB

[ACM Press the 23rd international confer

[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - Robust probabilistic projections

✍ Archambeau, Cédric; Delannay, Nicolas; Verleysen, Michel 📂 Article 📅 2006 🏛 ACM Press ⚖ 264 KB

[ACM Press the 23rd international confer

[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - Robust probabilistic projections

✍ Archambeau, Cédric; Delannay, Nicolas; Verleysen, Michel 📂 Article 📅 2006 🏛 ACM Press ⚖ 264 KB

Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, probabilistic reformulations of these methods have been proposed . They are based on a Gaussian density model and are ther

[ACM Press the 23rd international confer

[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - An empirical comparison of supervised learning algorithms

✍ Caruana, Rich; Niculescu-Mizil, Alexandru 📂 Article 📅 2006 🏛 ACM Press ⚖ 157 KB

[ACM Press the 23rd international confer

[ACM Press the 23rd international conference - Pittsburgh, Pennsylvania (2006.06.25-2006.06.29)] Proceedings of the 23rd international conference on Machine learning - ICML '06 - An empirical comparison of supervised learning algorithms

✍ Caruana, Rich; Niculescu-Mizil, Alexandru 📂 Article 📅 2006 🏛 ACM Press ⚖ 157 KB

A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog Project in the early 90's. We present a large-scale empirical comparison between ten supervised learning methods: SVMs, n