From 7c547095950c69b221d9b5e2a46cea0e51ecd467 Mon Sep 17 00:00:00 2001
From: Ulrich <ulrich.kerzel@rwth-aachen.de>
Date: Mon, 8 May 2023 09:41:16 +0200
Subject: [PATCH] change url to PDF for census data
---
datascienceintro/Classification_DecisionTree.ipynb | 2 +-
datascienceintro/DataScience_Stats_Correlation_2Dice.ipynb | 3 ++-
datascienceintro/cluster.ipynb | 2 +-
datascienceintro/index.ipynb | 2 +-
4 files changed, 5 insertions(+), 4 deletions(-)
diff --git a/datascienceintro/Classification_DecisionTree.ipynb b/datascienceintro/Classification_DecisionTree.ipynb
index 7505fde..1401a85 100644
--- a/datascienceintro/Classification_DecisionTree.ipynb
+++ b/datascienceintro/Classification_DecisionTree.ipynb
@@ -11,7 +11,7 @@
"\n",
"In this example, we look at the performance of a simple [decision tree](https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html) from the Scikit-Learn package.\n",
"\n",
- "We will use the [adult dataset](https://archive.ics.uci.edu/ml/datasets/adult) that focuses on a (binary) classification task whether or not a person makes more than 50k USD per year. The data are taken from a 1994 census and were first discussed in the paper [Ron Kohavi, \"Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid\", Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996](https://www.academia.edu/download/40088603/Scaling_Up_the_Accuracy_of_Naive-Bayes_C20151116-5477-1fw84ob.pdf)\n",
+ "We will use the [adult dataset](https://archive.ics.uci.edu/ml/datasets/adult) that focuses on a (binary) classification task whether or not a person makes more than 50k USD per year. The data are taken from a 1994 census and were first discussed in the paper [Ron Kohavi, \"Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid\", Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, 1996](https://staff.icar.cnr.it/manco/Teaching/2005/datamining/articoli/nbtree.pdf)\n",
"\n",
"The data have a number of categorial and numerical features.\n",
"We can access the data directly from the archive (or use a local copy)."
diff --git a/datascienceintro/DataScience_Stats_Correlation_2Dice.ipynb b/datascienceintro/DataScience_Stats_Correlation_2Dice.ipynb
index ecd8719..662f2e9 100644
--- a/datascienceintro/DataScience_Stats_Correlation_2Dice.ipynb
+++ b/datascienceintro/DataScience_Stats_Correlation_2Dice.ipynb
@@ -307,7 +307,8 @@
"name": "python3"
},
"language_info": {
- "name": "python"
+ "name": "python",
+ "version": "3.10.6"
}
},
"nbformat": 4,
diff --git a/datascienceintro/cluster.ipynb b/datascienceintro/cluster.ipynb
index 60d546f..d18c2cb 100644
--- a/datascienceintro/cluster.ipynb
+++ b/datascienceintro/cluster.ipynb
@@ -707,7 +707,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.6 (main, Nov 14 2022, 16:10:14) [GCC 11.3.0]"
+ "version": "3.10.6"
},
"orig_nbformat": 4,
"vscode": {
diff --git a/datascienceintro/index.ipynb b/datascienceintro/index.ipynb
index 49e0b58..ae1958a 100644
--- a/datascienceintro/index.ipynb
+++ b/datascienceintro/index.ipynb
@@ -21,7 +21,7 @@
},
"language_info": {
"name": "python",
- "version": "3.10.6 (main, Nov 14 2022, 16:10:14) [GCC 11.3.0]"
+ "version": "3.10.6"
},
"orig_nbformat": 4,
"vscode": {
--
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