The search space for the feature selection problem in decision tree learning is the lattice of subsets of the available features. We design an exact enumeration procedure of the subsets of features that lead to all and only the distinct decision trees built by a greedy top-down decision tree induction algorithm. The procedure stores, in the worst case, a number of trees linear in the number of features. By exploiting a further pruning of the search space, we design a complete procedure for finding δ-acceptable feature subsets, which depart by at most δ from the best estimated error over any feature subset. Feature subsets with the best estimated error are called best feature subsets. Our results apply to any error estimator function, but ex...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
The search space for the feature selection problem in decision tree learning is the lattice of subse...
The search space for the feature selection problem in decision tree learning is the lattice of subse...
In the wrapper approach to feature subset selection, a search for an optimal set of features is made...
AbstractIn the feature subset selection problem, a learning algorithm is faced with the problem of s...
In the feature subset selection problem, a learning algorithm is faced with the problem of selecting...
AbstractFeature selection is an effective technique in dealing with dimensionality reduction. For cl...
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for...
Given the increasing size and complexity of datasets needed to train machine learning algorithms, it...
Recent work has shown that feature subset selection can have a position affect on the performance of...
International audienceThis paper formalizes Feature Selection as a Reinforcement Learning problem, l...
AbstractFeature selection is a technique to choose a subset of variables from the multidimensional d...
Dimensionality reduction of the problem space through detection and removal of variables, contributi...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...
The search space for the feature selection problem in decision tree learning is the lattice of subse...
The search space for the feature selection problem in decision tree learning is the lattice of subse...
In the wrapper approach to feature subset selection, a search for an optimal set of features is made...
AbstractIn the feature subset selection problem, a learning algorithm is faced with the problem of s...
In the feature subset selection problem, a learning algorithm is faced with the problem of selecting...
AbstractFeature selection is an effective technique in dealing with dimensionality reduction. For cl...
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for...
Given the increasing size and complexity of datasets needed to train machine learning algorithms, it...
Recent work has shown that feature subset selection can have a position affect on the performance of...
International audienceThis paper formalizes Feature Selection as a Reinforcement Learning problem, l...
AbstractFeature selection is a technique to choose a subset of variables from the multidimensional d...
Dimensionality reduction of the problem space through detection and removal of variables, contributi...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
An emerging trend in feature selection is the development of two-objective algorithms that analyze t...
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer S...