started 10

Author: tdpetrou

Introduction to Statistical Learning/Chapter 10.ipynb

@@ -59,7 +59,15 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Chapter 10: Unsupervised Learning"
+    "# Chapter 10: Unsupervised Learning\n",
+    "Book has been about supervised learning until now. No response variable. Will try and find interesting things in explanatory variables. Chapter will focus on principal components analysis and clustering. No always an exact goal.\n",
+    "\n",
+    "## Principal Components Analysis\n",
+    "Chapter 6 covered principal component regression where the original features were mapped to a smaller feature space that are then used as inputs into linear regression solved normally through least squares.\n",
+    "\n",
+    "PCA can be used to visualize high dimensional data in 2 or 3 dimensions. The first component is a weighted linear combination of all the original features where the sum of the squared weights equals 1. These weights are the loading factors. The loading factors of the first principal component maximize the weighted sum of the features for each observation.\n",
+    "\n",
+    "The second principal component is uncorrelated with the first which makes it orthogonal to it."
    ]
   },
   {