How to make training and testing data files for LIBSVM and/or TinySVM - libsvm

Question

when I open the sample files for training data of LIBSVM, I can't understand the file structure. Can someone please show me how to make it ?
Below is my training data to predict song writers of a song(as an example):
Feature 1: Number of "love" word in the lyric
Feature 2: Number of "friend" word in the lyric
Feature 3: Number of "zone" word in the lyrics
Training data:
Song A (3, 0, 0), song writer is David
Song B (0, 3, 1), song writer is Peter
Song C (1, 3, 1), song writer is Tom
Testing data:
Song D (3, 0, 1)
Thank you very much.

Answer 1

Libsvm ReadMe file can help you
The training data must be something like this
label feature1:value1 feature2:value2 ..... -1:? (? can be any number)
but in the Libsvm there is something called svm_node that do the same thing:
sample code in java:
for (int k = 0; k < dataCount; k++) {
prob.x[k] = new svm_node[features.length];
for (int j = 0; j < features.length; j++) {
svm_node node = new svm_node();
node.index = featuresIndex[j];
node.value = features[j];
prob.x[k][j] = node;
}
prob.y[k] = lable;
}

Answer 2

In this problem of classification we have three classes for our whole dataset David, Peter, Tom and we assign them values 0, 1 and 2 receptively.
The format of data set will be.
[label] [feature number] : [the no of times that feature occurs] .... ....
Our training data file will look like this.
0 1:3 2:0 3:0
1 1:0 3:1 3:1
2 1:1 2:3 3:1
This file can be used to train our model. In this file there are 3 rows and four columns, the first column represents the actual result and the other columns represent the feature number : the number of times that feature occurs.
The testing data will be treated as.
1:3 2:0 3:1
this will be passed to svm model and then prediction can be drawn.