spark MultivariateStatisticalSummary 源码
spark MultivariateStatisticalSummary 代码
文件路径：/mllib/src/main/scala/org/apache/spark/mllib/stat/MultivariateStatisticalSummary.scala
/*
* 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.
*/
package org.apache.spark.mllib.stat
import org.apache.spark.annotation.Since
import org.apache.spark.mllib.linalg.Vector
/**
* Trait for multivariate statistical summary of a data matrix.
*/
@Since("1.0.0")
trait MultivariateStatisticalSummary {
/**
* Sample mean vector.
*/
@Since("1.0.0")
def mean: Vector
/**
* Sample variance vector. Should return a zero vector if the sample size is 1.
*/
@Since("1.0.0")
def variance: Vector
/**
* Sample size.
*/
@Since("1.0.0")
def count: Long
/**
* Sum of weights.
*/
@Since("3.0.0")
def weightSum: Double
/**
* Number of nonzero elements (including explicitly presented zero values) in each column.
*/
@Since("1.0.0")
def numNonzeros: Vector
/**
* Maximum value of each column.
*/
@Since("1.0.0")
def max: Vector
/**
* Minimum value of each column.
*/
@Since("1.0.0")
def min: Vector
/**
* Euclidean magnitude of each column
*/
@Since("1.2.0")
def normL2: Vector
/**
* L1 norm of each column
*/
@Since("1.2.0")
def normL1: Vector
}
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