Update

README.md

@@ -25,6 +25,7 @@ sure that it has a shape `(seq_len, n_dims)`.
 ```python
 import numpy as np
 import roerich
+import roerich.algorithms
 
 X, label = roerich.generate_dataset(period=2000, N_tot=20000)
 T = np.arange(len(X))
@@ -34,10 +35,10 @@ To perform change point detection, you can use two algorithms: `CLF` or `RuLSIF`
 followed by calling a `predict method`: 
 
 ```python
-cpd = roerich.OnlineNNClassifier(net='default', scaler="default", metric="KL_sym",
-                  periods=1, window_size=10, lag_size=500, step=10, n_epochs=10,
-                  lr=0.1, lam=0.0001, optimizer="Adam"
-                 )
+cpd = roerich.algorithms.OnlineNNClassifier(net='default', scaler="default", metric="KL_sym",
+                                            periods=1, window_size=10, lag_size=500, step=10, n_epochs=10,
+                                            lr=0.1, lam=0.0001, optimizer="Adam"
+                                            )
 
 # Detect change points
 score, peaks = cpd.predict(X)
@@ -49,10 +50,6 @@ roerich.display(X, T, label, score, T, peaks)
 ```
 ![](images/demo.png)
 
-## Changelog
-
-See the [changelog](https://github.com/HSE-LAMBDA/roerich/blob/master/CHANGELOG.md) for a history of notable changes to roerich.
-
 ## Thanks to all our contributors
 
 <a href="https://github.com/HSE-LAMBDA/roerich/graphs/contributors">
@@ -87,4 +84,4 @@ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-```
+```