Created using Colaboratory

Author: adhishagc

Genetic_Algorithm_Assignment.ipynb

@@ -35,29 +35,18 @@
         "colab_type": "text"
       },
       "source": [
-        "### **Debug Process**"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "q4o89dgjjjXb",
-        "colab_type": "text"
-      },
-      "source": [
+        "## **Table of Contents**\n",
+        "\n",
+        "---\n",
+        "\n",
+        "\n",
+        "1.   **Importing Libraries**\n",
+        "2.   **Access to Google Drive**\n",
+        "3.**Function Definitions**\n",
+        "4. **Running the Model**\n",
         "\n",
-        "1. Check algorithm structure is available. Each phase\n",
-        "\t1. Create Population\n",
-        "\t2. Evaluate Fitness of Each Chromosome in the Population\n",
-        "\t3. Create New Population by :\n",
-        "\t\t1. Select 2 Parents\n",
-        "\t\t2. Crossover\n",
-        "\t\t3. Mutate\n",
-        "\t\t4. Replace to the Population\n",
-        "\t4. Test if End condition is satisified\n",
-        "\t5. If Yes,end otherwise iterate with the new Population\n",
-        "\t\n",
-        "2. Functionality of each section\n"
+        "\n",
+        "\n"
       ]
     },
     {
@@ -89,7 +78,7 @@
         }
       },
       "source": [
-        "#access to google drive\n",
+        "#Access to google drive. The Video Store dataset was uploaded to google drive.\n",
         "from google.colab import drive\n",
         "drive.mount('/content/gdrive')"
       ],
@@ -112,7 +101,7 @@
         "colab": {}
       },
       "source": [
-        "#load dataset to a dataframe\n",
+        "#The dataset is load dataset to a dataframe\n",
         "df = pd.read_csv('/content/gdrive/My Drive/Genetic Algorithms/Assignment 01/dataset.csv')"
       ],
       "execution_count": 0,
@@ -265,7 +254,8 @@
         "colab_type": "text"
       },
       "source": [
-        "### **Population Creation Function**"
+        "### **Population Creation Function**\n",
+        "A dataframe which consists of the entire population is returned when this function is called. The structure would be of 1 column to label the chromosome number and the remaining 10 columns will represent the file number of the dataset. The returned dataframe (population) will consist of random 0 or 1 values in the  chromosome."
       ]
     },
     {
@@ -278,10 +268,9 @@
       "source": [
         "# function for init population\n",
         "def createInitPop(popSize):\n",
-        "  chrom = [i for i in range(1,popSize+1)]\n",
-        "  #emp = [0 for i in range(0,popSize)]\n",
+        "  #array of data to represent the chromosomes and random file labellings\n",
         "  values ={\n",
-        "    'chromosome':chrom,\n",
+        "    'chromosome':[i for i in range(1,popSize+1)],\n",
         "    'file 1':[random.randint(0, 1) for _ in range(popSize)],\n",
         "    'file 2':[random.randint(0, 1) for _ in range(popSize)],\n",
         "    'file 3':[random.randint(0, 1) for _ in range(popSize)],\n",
@@ -293,7 +282,11 @@
         "    'file 9':[random.randint(0, 1) for _ in range(popSize)],\n",
         "    'file 10':[random.randint(0, 1) for _ in range(popSize)],\n",
         "  }\n",
-        "  return pd.DataFrame(values)  "
+        "  #convert the array of population to a dataframe\n",
+        "  values = pd.DataFrame(values)\n",
+        "  \n",
+        "  #return the dataframe\n",
+        "  return values"
       ],
       "execution_count": 0,
       "outputs": []