Clarify that FM implementation is not really 'higher' order

Author: vene

README.rst

@@ -3,7 +3,7 @@
 polylearn
 =========
 
-A library for higher-order **factorization machines** and **polynomial networks**
+A library for **factorization machines** and **polynomial networks**
 for classification and regression in Python.
 
 .. image:: https://travis-ci.org/scikit-learn-contrib/polylearn.svg?branch=master

doc/references.rst

@@ -6,8 +6,8 @@ polylearn reference
 
 .. _factorization_machine:
 
-(Higher Order) Factorization Machines
--------------------------------------
+Factorization Machines
+----------------------
 
 .. automodule:: polylearn.factorization_machine
    :no-members:

polylearn/factorization_machine.py

@@ -143,7 +143,7 @@ def _predict(self, X):
 
 class FactorizationMachineRegressor(_BaseFactorizationMachine,
                                     _PolyRegressorMixin):
-    """Higher order factorization machine for regression (with squared loss).
+    """Factorization machine for regression (with squared loss).
 
     Parameters
     ----------
@@ -257,7 +257,7 @@ def __init__(self, degree=2, n_components=2, alpha=1, beta=1, tol=1e-6,
 
 class FactorizationMachineClassifier(_BaseFactorizationMachine,
                                      _PolyClassifierMixin):
-    """Higher order factorization machine for classification.
+    """Factorization machine for classification.
 
     Parameters
     ----------

setup.py

@@ -13,7 +13,7 @@
 
 
 DISTNAME = 'polylearn'
-DESCRIPTION = ("Higher-order factorization machines and polynomial networks "
+DESCRIPTION = ("Factorization machines and polynomial networks "
                "for classification and regression in Python.")
 LONG_DESCRIPTION = open('README.rst').read()
 MAINTAINER = 'Vlad Niculae'