From c7b52010dfd0a765376464ebc43d5cdd3b80a460 Mon Sep 17 00:00:00 2001
From: DB Tsai <dbtsai@alpinenow.com>
Date: Tue, 5 Aug 2014 23:32:29 -0700
Subject: [PATCH] [MLlib] Use this.type as return type in k-means' builder
pattern
to ensure that the return object is itself.
Author: DB Tsai <dbtsai@alpinenow.com>
Closes #1796 from dbtsai/dbtsai-kmeans and squashes the following commits:
658989e [DB Tsai] Alpine Data Labs
---
.../org/apache/spark/mllib/clustering/KMeans.scala | 12 ++++++------
1 file changed, 6 insertions(+), 6 deletions(-)
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
index db425d866b..fce8fe29f6 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/clustering/KMeans.scala
@@ -52,13 +52,13 @@ class KMeans private (
def this() = this(2, 20, 1, KMeans.K_MEANS_PARALLEL, 5, 1e-4)
/** Set the number of clusters to create (k). Default: 2. */
- def setK(k: Int): KMeans = {
+ def setK(k: Int): this.type = {
this.k = k
this
}
/** Set maximum number of iterations to run. Default: 20. */
- def setMaxIterations(maxIterations: Int): KMeans = {
+ def setMaxIterations(maxIterations: Int): this.type = {
this.maxIterations = maxIterations
this
}
@@ -68,7 +68,7 @@ class KMeans private (
* initial cluster centers, or "k-means||" to use a parallel variant of k-means++
* (Bahmani et al., Scalable K-Means++, VLDB 2012). Default: k-means||.
*/
- def setInitializationMode(initializationMode: String): KMeans = {
+ def setInitializationMode(initializationMode: String): this.type = {
if (initializationMode != KMeans.RANDOM && initializationMode != KMeans.K_MEANS_PARALLEL) {
throw new IllegalArgumentException("Invalid initialization mode: " + initializationMode)
}
@@ -83,7 +83,7 @@ class KMeans private (
* return the best clustering found over any run. Default: 1.
*/
@Experimental
- def setRuns(runs: Int): KMeans = {
+ def setRuns(runs: Int): this.type = {
if (runs <= 0) {
throw new IllegalArgumentException("Number of runs must be positive")
}
@@ -95,7 +95,7 @@ class KMeans private (
* Set the number of steps for the k-means|| initialization mode. This is an advanced
* setting -- the default of 5 is almost always enough. Default: 5.
*/
- def setInitializationSteps(initializationSteps: Int): KMeans = {
+ def setInitializationSteps(initializationSteps: Int): this.type = {
if (initializationSteps <= 0) {
throw new IllegalArgumentException("Number of initialization steps must be positive")
}
@@ -107,7 +107,7 @@ class KMeans private (
* Set the distance threshold within which we've consider centers to have converged.
* If all centers move less than this Euclidean distance, we stop iterating one run.
*/
- def setEpsilon(epsilon: Double): KMeans = {
+ def setEpsilon(epsilon: Double): this.type = {
this.epsilon = epsilon
this
}
--
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