From c235e02d5943afab26d13bebeefab58e3c6b0c38 Mon Sep 17 00:00:00 2001
From: dsp <parkds7@gmail.com>
Date: Sat, 5 Oct 2019 23:58:26 -0400
Subject: [PATCH 1/2] mimic noise feature addition

---
 mlrose/algorithms.py |  7 ++++++-
 mlrose/opt_probs.py  | 16 +++++++++++++++-
 2 files changed, 21 insertions(+), 2 deletions(-)

diff --git a/mlrose/algorithms.py b/mlrose/algorithms.py
index a00d431d..88142a01 100644
--- a/mlrose/algorithms.py
+++ b/mlrose/algorithms.py
@@ -456,7 +456,7 @@ def genetic_alg(problem, pop_size=200, mutation_prob=0.1, max_attempts=10,
 
 
 def mimic(problem, pop_size=200, keep_pct=0.2, max_attempts=10,
-          max_iters=np.inf, curve=False, random_state=None, fast_mimic=False):
+          max_iters=np.inf, curve=False, random_state=None, fast_mimic=False,noise=0):
     """Use MIMIC to find the optimum for a given optimization problem.
 
     Parameters
@@ -539,6 +539,11 @@ def mimic(problem, pop_size=200, keep_pct=0.2, max_attempts=10,
     else:
         problem.mimic_speed=fast_mimic
 
+    if (noise < 0) or (noise > 0.1):
+        raise Exception("""noise must be between 0 and 0.1.""")
+    else:
+        problem.noise=noise
+
     # Initialize problem, population and attempts counter
     problem.reset()
     problem.random_pop(pop_size)
diff --git a/mlrose/opt_probs.py b/mlrose/opt_probs.py
index f3831b7d..32ef21d1 100644
--- a/mlrose/opt_probs.py
+++ b/mlrose/opt_probs.py
@@ -364,10 +364,24 @@ def eval_node_probs(self):
                 if not len(subset):
                     probs[i, j] = 1/self.max_val
                 else:
-                    probs[i, j] = np.histogram(subset[:, i],
+
+                    temp_probs = np.histogram(subset[:, i],
                                                np.arange(self.max_val + 1),
                                                density=True)[0]
 
+                    #Check if noise argument is not default (in epsilon)
+                    if self.noise!=0:
+                        #Add noise, from the mimic argument "noise"
+                        temp_probs = (temp_probs + self.noise)
+                        #All probability adds up to one
+                        temp_probs=np.divide(temp_probs,np.sum(temp_probs))
+                        #Handle floating point error to ensure probability adds up to 1
+                        if sum(temp_probs) != 1.0:
+                            temp_probs = np.divide(temp_probs, np.sum(temp_probs))
+                        #Set probability
+
+                    probs[i, j]=temp_probs
+
         # Update probs and parent
         self.node_probs = probs
         self.parent_nodes = parent

From ff1344facc5472c707b12947ef168f09bd29e6c0 Mon Sep 17 00:00:00 2001
From: dsp <parkds7@gmail.com>
Date: Sun, 6 Oct 2019 14:33:01 -0400
Subject: [PATCH 2/2]  mimic noise description added, included noise for
 discreteopt initialization

---
 mlrose/algorithms.py | 3 +++
 mlrose/opt_probs.py  | 1 +
 2 files changed, 4 insertions(+)

diff --git a/mlrose/algorithms.py b/mlrose/algorithms.py
index 88142a01..1b0faf43 100644
--- a/mlrose/algorithms.py
+++ b/mlrose/algorithms.py
@@ -484,6 +484,9 @@ def mimic(problem, pop_size=200, keep_pct=0.2, max_attempts=10,
     fast_mimic: bool, default: False
         Activate fast mimic mode to compute the mutual information in vectorized form
         Faster speed but requires more memory.
+    noise: float, default: 0
+        Adds noise to the probability and conditional probability estimates.
+        0.01 corresponds to 1% noise.
 
     Returns
     -------
diff --git a/mlrose/opt_probs.py b/mlrose/opt_probs.py
index d0a68d8e..00a0e5a2 100644
--- a/mlrose/opt_probs.py
+++ b/mlrose/opt_probs.py
@@ -272,6 +272,7 @@ def __init__(self, length, fitness_fn, maximize=True, max_val=2):
         self.sample_order = []
         self.prob_type = 'discrete'
         self.mimic_speed = False
+        self.noise=0
 
     def eval_node_probs(self):
         """Update probability density estimates.