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» Evaluating learning algorithms and classifiers
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92
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CVPR
2010
IEEE
15 years 9 months ago
Unsupervised Learning of Invariant Features Using Video
We present an algorithm that learns invariant features from real data in an entirely unsupervised fashion. The principal benefit of our method is that it can be applied without hu...
David Stavens, Sebastian Thrun
114
Voted
NIPS
2008
15 years 2 months ago
An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis
We study the problem of domain transfer for a supervised classification task in mRNA splicing. We consider a number of recent domain transfer methods from machine learning, includ...
Gabriele Schweikert, Christian Widmer, Bernhard Sc...
ICML
2000
IEEE
16 years 1 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
97
Voted
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
15 years 6 months ago
Improving the human readability of features constructed by genetic programming
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming a...
Matthew Smith, Larry Bull
96
Voted
WWW
2007
ACM
16 years 1 months ago
Demographic prediction based on user's browsing behavior
Demographic information plays an important role in personalized web applications. However, it is usually not easy to obtain this kind of personal data such as age and gender. In t...
Jian Hu, Hua-Jun Zeng, Hua Li, Cheng Niu, Zheng Ch...