[liblinear] 68/123: Correct numerous mistakes in man pages

[Christian Kastner]

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chrisk-guest pushed a commit to branch master
in repository liblinear.

commit c46121c037e3b79b2bd08d76e3f7a93c202d400c
Author: Christian Kastner <debian at kvr.at>
Date:   Tue Mar 8 21:52:07 2011 +0100

    Correct numerous mistakes in man pages
    
    As identified by Chen-Tse Tsai (thanks!)
---
 debian/liblinear-predict.1 |  4 ++--
 debian/liblinear-train.1   | 14 +++++++-------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/debian/liblinear-predict.1 b/debian/liblinear-predict.1
index bdf7652..7c744ed 100644
--- a/debian/liblinear-predict.1
+++ b/debian/liblinear-predict.1
@@ -1,5 +1,5 @@
 .\"                                      Hey, EMACS: -*- nroff -*-
-.TH LIBLINEAR-PREDICT 1 "June 16, 2010"
+.TH LIBLINEAR-PREDICT 1 "March 08, 2011"
 .SH NAME
 liblinear-predict \- Make predictions based on a trained linear classifier model
 .SH SYNOPSIS
@@ -28,7 +28,7 @@ Output probability estimates (for logistic regression only):
 .sp
 .RS 10
 .nf
- libpredict \-b 1 test_file data_file.model output_file
+ liblinear-predict \-b 1 test_file data_file.model output_file
 .fi
 .RE
 .SH SEE ALSO
diff --git a/debian/liblinear-train.1 b/debian/liblinear-train.1
index 05dc053..4beafac 100644
--- a/debian/liblinear-train.1
+++ b/debian/liblinear-train.1
@@ -1,5 +1,5 @@
 .\"                                      Hey, EMACS: -*- nroff -*-
-.TH LIBLINEAR-TRAIN 1 "June 16, 2010"
+.TH LIBLINEAR-TRAIN 1 "March 08, 2011"
 .SH NAME
 liblinear-train \- train a linear classifier and produce a model
 .SH SYNOPSIS
@@ -14,7 +14,7 @@ model suitable for use with \fBliblinear-predict\fP(1).
 \fImodel_file\fP is the file to which the model will be saved. If
 \fImodel_file\fP is not provided, it defaults to \fItraining_set_file.model\fP.
 
-To obtain good performances, sometimes one needs to scale that data. This can be
+To obtain good performances, sometimes one needs to scale the data. This can be
 done with \fBsvm-scale\fP(1).
 .SH OPTIONS
 A summary of options is included below.
@@ -76,9 +76,9 @@ function (default: \fB0.01\fP)
 .TP
 .B \-B \fIbias\fP
 If \fIbias\fP >= 0, then instance x becomes [x; bias]; if \fIbias\fP < 0, then
-no bias term is added (default: \fB1\fP)
+no bias term is added (default: \fB-1\fP)
 .TP
-.B \-w \fIi\fP \fIweight\fP
+.B \-w\fIi\fP \fIweight\fP
 Weight-adjusts the parameter C of class \fIi\fP by the value \fIweight\fP
 .TP
 .B \-v \fIn\fP
@@ -120,11 +120,11 @@ positive    negative        Cp  Cn
 .br
 class 1     class 2,3,4     20  10
 .br
-class 2     class 1,3,4     20  10
+class 2     class 1,3,4     50  10
 .br
 class 3     class 1,2,4     20  10
 .br
-class 4     class 1,2,3     20  10
+class 4     class 1,2,3     10  10
 .RE
 .sp
 .RS 10
@@ -134,7 +134,7 @@ class 4     class 1,2,3     20  10
 .RE
 .sp
 If there are only two classes, we train ONE model. The C values for the two
-calsses are 10 and 50:
+classes are 10 and 50:
 .sp
 .RS 10
 .nf

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