Update README.md

Author: jundongl

README.md

@@ -3,12 +3,10 @@ scikit-feast
 ===============================
 Feature selection repository built on scikit-learn (DMML Lab@ASU). 
 
-The feature selection repository is designed to collect some widely used feature selection algorithms that have been developed in the feature selection research to serve as a platform for facilitating their application, comparison and joint study. The feature selection repository also effectively assists researchers to achieve more reliable evaluation in the process of developing new feature selection algorithms. We develop the open source feature selection repository scikit-feast by one of the most popular programming language python. It contains more than 40 popular feature selection algorithms, including most traditional feature selection algorithms and some structural and streaming feature selection algorithms. It is built upon one widely used machine learning package scikit-learn and two scientific computing packages Numpy and Scipy.
+The feature selection repository is designed to collect some widely used feature selection algorithms that have been developed in the feature selection research to serve as a platform for facilitating their application, comparison and joint study. The feature selection repository also effectively assists researchers to achieve more reliable evaluation in the process of developing new feature selection algorithms. We develop the open source feature selection repository scikit-feast by one of the most popular programming language - python. It contains more than 40 popular feature selection algorithms, including most traditional feature selection algorithms and some structural and streaming feature selection algorithms. It is built upon one widely used machine learning package scikit-learn and two scientific computing packages Numpy and Scipy.
 
 ##Installing scikit-feast
-
 ###Prerequisites:
-
 Python 2.7
 
 NumPy
@@ -18,18 +16,15 @@ SciPy
 Scikit-learn
 
 ###Steps:
-After you download scikit-feast-1.0.0.zip, unpack the archive. Additionally, the scikit-feast root directory will contain a setup script setup.py and a file named README.txt.
+After you download scikit-feast-1.0.0.zip from the project website (http://featureselection.asu.edu/scikit-feast/), unzip the file. Then the scikit-feast root directory will contain a setup script setup.py and a file named README.txt.
 
-For Linux, under the scikit-feast root directory building and installing the module distribution is a simple matter of running one command from a terminal：
+For Linux, under the scikit-feast root directory, you can build and install the module by the following command from a terminal：
 python setup.py install
 
-For Windows, this command should be run from a command prompt window (Start->Accessories), under the scikit-feast root directory:
+For Windows, you can also run the command prompt window (Start->Accessories), under the scikit-feast root directory:
 setup.py install
 
-If all these things are true, then you already know how to build and install the modules you have just downloaded
-
 ##Project website
-
 Instructions of using this package can be found in our project webpage at http://featureselection.asu.edu/scikit-feast/
 
 ##Citing
@@ -45,17 +40,8 @@ If you find scikit-feast feature selection reposoitory useful in your research,
     }
 
 ##Contact
-
 Jundong Li
-
 E-mail: [email protected]
 
 Kewei Cheng
-
 E-mail: [email protected]
-
-Huan Liu
-
-E-mail: [email protected]
-
-Physical address: Brickyard Suite 553 (CIDSE), 699 South Mill Ave, Tempe, AZ 85281