From 72634f27e3110fd7f5bfca498752f69d0b1f873c Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Thu, 5 Nov 2015 08:59:06 -0800
Subject: [PATCH] [MINOR][ML][DOC] Rename weights to coefficients in user guide
We should use ```coefficients``` rather than ```weights``` in user guide that freshman can get the right conventional name at the outset. mengxr vectorijk
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #9493 from yanboliang/docs-coefficients.
---
docs/ml-linear-methods.md | 24 ++++++++++++------------
1 file changed, 12 insertions(+), 12 deletions(-)
diff --git a/docs/ml-linear-methods.md b/docs/ml-linear-methods.md
index 4e94e2f9c7..16e2ee7129 100644
--- a/docs/ml-linear-methods.md
+++ b/docs/ml-linear-methods.md
@@ -71,8 +71,8 @@ val lr = new LogisticRegression()
// Fit the model
val lrModel = lr.fit(training)
-// Print the weights and intercept for logistic regression
-println(s"Weights: ${lrModel.weights} Intercept: ${lrModel.intercept}")
+// Print the coefficients and intercept for logistic regression
+println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
{% endhighlight %}
</div>
@@ -105,8 +105,8 @@ public class LogisticRegressionWithElasticNetExample {
// Fit the model
LogisticRegressionModel lrModel = lr.fit(training);
- // Print the weights and intercept for logistic regression
- System.out.println("Weights: " + lrModel.weights() + " Intercept: " + lrModel.intercept());
+ // Print the coefficients and intercept for logistic regression
+ System.out.println("Coefficients: " + lrModel.coefficients() + " Intercept: " + lrModel.intercept());
}
}
{% endhighlight %}
@@ -124,8 +124,8 @@ lr = LogisticRegression(maxIter=10, regParam=0.3, elasticNetParam=0.8)
# Fit the model
lrModel = lr.fit(training)
-# Print the weights and intercept for logistic regression
-print("Weights: " + str(lrModel.weights))
+# Print the coefficients and intercept for logistic regression
+print("Coefficients: " + str(lrModel.coefficients))
print("Intercept: " + str(lrModel.intercept))
{% endhighlight %}
</div>
@@ -258,8 +258,8 @@ val lr = new LinearRegression()
// Fit the model
val lrModel = lr.fit(training)
-// Print the weights and intercept for linear regression
-println(s"Weights: ${lrModel.weights} Intercept: ${lrModel.intercept}")
+// Print the coefficients and intercept for linear regression
+println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
// Summarize the model over the training set and print out some metrics
val trainingSummary = lrModel.summary
@@ -302,8 +302,8 @@ public class LinearRegressionWithElasticNetExample {
// Fit the model
LinearRegressionModel lrModel = lr.fit(training);
- // Print the weights and intercept for linear regression
- System.out.println("Weights: " + lrModel.weights() + " Intercept: " + lrModel.intercept());
+ // Print the coefficients and intercept for linear regression
+ System.out.println("Coefficients: " + lrModel.coefficients() + " Intercept: " + lrModel.intercept());
// Summarize the model over the training set and print out some metrics
LinearRegressionTrainingSummary trainingSummary = lrModel.summary();
@@ -330,8 +330,8 @@ lr = LinearRegression(maxIter=10, regParam=0.3, elasticNetParam=0.8)
# Fit the model
lrModel = lr.fit(training)
-# Print the weights and intercept for linear regression
-print("Weights: " + str(lrModel.weights))
+# Print the coefficients and intercept for linear regression
+print("Coefficients: " + str(lrModel.coefficients))
print("Intercept: " + str(lrModel.intercept))
# Linear regression model summary is not yet supported in Python.
--
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