blob: 4fc3ef482d6aba0533b40e87e223bc559eef4921 [file] [log] [blame]
#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
#-------------------------------------------------------------
# Scale and center individual features in the input matrix
# (column-wise) using z-score to scale the values.
# -----------------------------------------------------------------------------
# NAME TYPE DEFAULT MEANING
# -----------------------------------------------------------------------------
# X Matrix --- Input feature matrix
# center Boolean TRUE Indicates whether or not to center the feature matrix
# scale Boolean TRUE Indicates whether or not to scale the feature matrix
# -----------------------------------------------------------------------------
# Y Matrix --- Output feature matrix with K columns
# -----------------------------------------------------------------------------
m_scale = function(Matrix[Double] X, Boolean center, Boolean scale) return (Matrix[Double] Y) {
if( center )
X = X - colMeans(X);
if (scale) {
cvars = colSums(X^2)/(nrow(X)-1);
#scale by std-dev and replace NaNs with 0's
X = replace(target=X/sqrt(cvars),
pattern=NaN, replacement=0);
}
Y = X;
}