Initial commit
Import the code for Fredholm kernel learning.
Update the README file.
Refactor the data set loading procedures
  + Remove the data generating procedures from util.py
  + Create DataSet class for storing the data sets, and change the corresponding callings
  + Rename the directory for config jsons to config
  + Add mnist.py for loading mnist datasets and the config file for experiments on MNIST
The changes should've be committed last time. See the description of last commit.
Update the mnist.py and util.py
+ Enable to add noise to existing data sets.
+ Add 20 news groups into the data sets.
+ Refactor the dataset.py a little bit.
+ Optimize the memory usage a little bit: basically remove the unnecessar data duplication in datasets.
+ Add SVD feature for 20 news group to reduce the memory usage.
+ Optimize the memory usage a little bit: basically remove the unnecessar data duplication in datasets.
+ Add SVD feature for 20 news group to reduce the memory usage.
+ fix a bug in laprlsc.py
Merge branch 'master' of https://github.com/queqichao/FredholmKernelLearning
* remove the line that used for debugging.
+ Refactor classification.py to enable profiling.
+ Fix a bug caused by memory optimizing.
+ Change the dtype to float32 to save some memory
+ Enable multi-layer Fredholm kernel, change the config file correspondingly.
+ Add a few functions for profiling.
+ Modify tsvm.py to allow sparse input.
+ Modify l2_kernel_classifier.py to deal with the issue of inversing a matrix with inf condition number.
+ Refactor laprlsc.py to reuse the code from l2_kernel_classifier.py
+ Fix bug in mnist.py, that did not convert uint8 to float properly.
Add FredholmKernelLearning as sub-repository