Piecewise-Linear Approximation for Feature Subset Selection in a Sequential Logit Model This paper concerns a method of selecting a subset of features for a sequential logit model. Tanaka and Nakagawa (2014) proposed a mixed integer quadratic ... T Sato,Y Takano,R Miyashiro - 《Journal of the...
experiments with two benchmark data sets show that the proposed method is similar in performance to the results reported earlier and is computationally less demanding in comparison to Genetic Alogrithm,another population based evolutionary search technique proposed eariler for feature subset selection by ...
Methods Information-theoretic subset selection One of the fundamental quantities in information theory that has been widely adopted for feature subset selection with filters is mutual information, which is given by: I(X; Y ) = y∈Y x∈X pX,Y (x, y) log pX,Y (x, y) pX(x) pY (y)...
开学季特惠,9月3日-11月30日,专业版用户每周AI豆3倍膨胀,快来领取吧! 摘要原文 Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classi...
This paper describes several known and some new methods for feature subset selection on large text data. Experimental comparison given on real-world data collected from Web users shows that characteristics of the problem domain and machine learning algor
In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, there is a strong requirement to select a subset of the features before building the classifier. This proposed technique treats feature subset selection as multi-objective ...
One possible criterion to judge the outcome of a feature subset selection is how much the selection depends on the training set. The Stability estimator runs the feature selection on different subsamples. It then computes the cumulative similarity of the selected feature subsets. Two possible measure...
About feature selectionIn machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable inputs. Narrowing the field of data helps ...
single-cell manifold-preserving feature selection (SCMER)57is an unsupervised feature selection method that selects a subset of features that best preserves the pairwise similarity matrix between cells defined in uniform manifold approximation and projection59based on all profiled features. To do so,...
single-cell manifold-preserving feature selection (SCMER)57is an unsupervised feature selection method that selects a subset of features that best preserves the pairwise similarity matrix between cells defined in uniform manifold approximation and projection59based on all profiled features. To do so,...