Matthieu/42a 234 module 04 ex 08 regularized logisitc (#184)

* fix (module04-ex08) add of lambda_ in signature constructor + Examples section to precise the expected behavior

* issue #176: taking into account ternary and class attribute supported_penalities

* inncrement of version

* indentation modification (tab instead of spaces)

module09/en.subject.tex

@@ -1057,12 +1057,16 @@ \section*{Instructions}
 	Description:
 		My personnal logistic regression to classify things.
 	"""
-	def __init__(self, theta, alpha=0.001, max_iter=1000, penalty='l2'):
-		self.alpha = alpha
+  supported_penalities = ['l2'] # We consider l2 penality only. One may wants to implement other penalities
+
+	def __init__(self, theta, alpha=0.001, max_iter=1000, penalty='l2', lambda_=1.0):
+		# Check on type, data type, value ... if necessary
+    self.alpha = alpha
 		self.max_iter = max_iter
 		self.theta = theta
-		self.penalty=penalty
-		... Your code ...
+		self.penalty = penalty
+    self.lambda_ = lambda_ if penality in self.supported_penalities else 0
+		#... Your code ...
 
 	... other methods ...
 \end{minted}
@@ -1075,6 +1079,49 @@ \section*{Instructions}
   \end{itemize}
 \end{itemize}
 
+% ================================= %
+\section*{Examples}
+% --------------------------------- %
+\begin{minted}[bgcolor=darcula-back,formatcom=\color{lightgrey},fontsize=\scriptsize]{python}
+from my_logistic_regression import MyLogisticRegression as mylogr
+
+theta = np.array([[-2.4], [-1.5], [0.3], [-1.4], [0.7]])
+
+# Example 1:
+model1 = mylogr(theta, lambda_=5.0)
+
+model1.penality
+# Output
+'l2'
+
+model1.lambda_
+# Output
+5.0
+
+# Example 2:
+model2 = mylogr(theta, penality=None)
+
+model2.penality
+# Output
+None
+
+model2.lambda_
+# Output
+0.0
+
+# Example 3:
+model3 = mylogr(theta, penality=None, lambda_=2.0)
+
+model3.penality
+# Output
+None
+
+model3.lambda_
+# Output
+0.0
+
+\end{minted}
+
 \hint{
   this is also a great use case for decorators...
 }