From b34fead9d6a9b0d5397fd30befbec8ae3c211fff Mon Sep 17 00:00:00 2001
From: Johnna Liu <156959054+JohnnaLiu999@users.noreply.github.com>
Date: Mon, 4 Nov 2024 02:07:03 -0500
Subject: [PATCH] Update lecture4-classification.ipynb

3
---
 aml-book/contents/lecture4-classification.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/aml-book/contents/lecture4-classification.ipynb b/aml-book/contents/lecture4-classification.ipynb
index 82a1da2..0e34fbe 100644
--- a/aml-book/contents/lecture4-classification.ipynb
+++ b/aml-book/contents/lecture4-classification.ipynb
@@ -151,7 +151,7 @@
       "from Fisher's paper. Note that it's the same as in R, but not as in the UCI\n",
       "Machine Learning Repository, which has two wrong data points.\n",
       "\n",
-      "This is perhaps the best known database to be found in the\n",
+      "This is perhaps the best-known database to be found in the\n",
       "pattern recognition literature.  Fisher's paper is a classic in the field and\n",
       "is referenced frequently to this day.  (See Duda & Hart, for example.)  The\n",
       "data set contains 3 classes of 50 instances each, where each class refers to a\n",
@@ -971,7 +971,7 @@
    "source": [
     "### Probabilistic Interpretations\n",
     "\n",
-    "Interestingly, the logistic model can also be interpreted as outputing a class membership probability. Specifically, the model defines a conditional probability $P_\\theta(y|x)$ distribution as follows:\n",
+    "Interestingly, the logistic model can also be interpreted as outputting a class membership probability. Specifically, the model defines a conditional probability $P_\\theta(y|x)$ distribution as follows:\n",
     "\n",
     "$$\n",
     "\\begin{align*}\n",