update README

Matlab/README.md

@@ -5,9 +5,11 @@ svm_train_matlab(parameters): The format of parameters is same as libsvm
 svm_predict_matlab(parameters): The format of parameters is same as libsvm
 	run svm predict according to parameters.
 Example:
->> n = ["-c", "10", "-g", "0.125", "test_dataset.txt", "test_dataset.model"]
->> m = cellstr(n)
->> svm_train_matlab(m)
->> n = ["test_dataset.txt", "test_dataset.model", "test_datset.out"]
->> m = cellstr(n)
->> svm_predict_matlab(m)
+```matlab
+n = ["-c", "10", "-g", "0.125", "test_dataset.txt", "test_dataset.model"]
+m = cellstr(n)
+svm_train_matlab(m)
+n = ["test_dataset.txt", "test_dataset.model", "test_datset.out"]
+m = cellstr(n)
+svm_predict_matlab(m)
+```

R/README.md

@@ -6,8 +6,10 @@ svm_predict_R(parameters): The format of parameters is same as libsvm
 	run svm predict according to parameters.
 
 Example:
-> source("svm.R")
-> c<-c("-c", "10", "-g", "0.125", "test_dataset.txt", "test_dataset.model")
-> svm_train_R(c)
-> c<-c("test_dataset.txt","test_dataset.model","test_dataset.out")
-> svm_predict_R(c)
+```R
+source("svm.R")
+c<-c("-c", "10", "-g", "0.125", "test_dataset.txt", "test_dataset.model")
+svm_train_R(c)
+c<-c("test_dataset.txt","test_dataset.model","test_dataset.out")
+svm_predict_R(c)
+```

python/README.md

@@ -9,9 +9,10 @@ svm_predict(labels, instances, 'model_file_name', 'output_file_name', parameters
 	use model_file_name to predict (labes, instances) according to parameters and save the result to output_file_name in dataset directory.
 
 Example:
->>> from svm import *
->>> y,x = svm_read_problem('mnist.scale')
->>> svm_train(y,x,'mnist.scale.model','-s 0 -t 2 -g 0.125 -c 10 -e 0.001')
->>> y,x=svm_read_problem('mnist.scale.t')
->>> svm_predict(y,x,'mnist.scale.model','mnist.scale.out')
-
+```python
+from svm import *
+y,x = svm_read_problem('mnist.scale')
+svm_train(y,x,'mnist.scale.model','-s 0 -t 2 -g 0.125 -c 10 -e 0.001')
+y,x=svm_read_problem('mnist.scale.t')
+svm_predict(y,x,'mnist.scale.model','mnist.scale.out')
+```