Refactor SOM class to RSOM class

Author: erogol

README.md

@@ -8,6 +8,45 @@ Rectifying Self Organizing Map (RSOM)
 RSOM is an algorithm as an extension of well-known Self Organizing Map (SOM). It mimics SOM clustering and additionally detects outliers in the given dataset in the cluster level or instance level.
 It is mainly used with image tasks but works as good with any other type of data.
 
+## Installation
+
+```
+git clone https://github.com/erogol/RSOM.git
+cd RSOM
+python setup.py install
+```
+
+or
+
+```
+pip install git+https://github.com/erogol/RSOM.git
+```
+
+## Usage
+
+Check ```sample_run.py``` for more.
+
+```python
+from rsom import RSOM
+
+# Load Iris dataset
+data = load_digits().data
+data = torch.from_numpy(data).float()
+print(data.shape)
+
+# Initialize SOM
+som = RSOM(data, alpha_max=0.05, num_units=49)
+
+# Train SOM
+som.train_batch(num_epoch=1000, verbose=True)
+
+# Get salient instances and units
+salient_insts = som.salient_insts()
+salient_units = som.salient_units()
+```
+
+
+
 ## Citation
 
 ```