1. Ahmet Selman Bozkır, Ebru Akçapınar SezerAhmet Selman Bozkır, Ebru Akçapınar Sezer
Hacettepe University Computer Engineering Dept.Hacettepe University Computer Engineering Dept.
Ankara -TurkeyAnkara -Turkey
20.5.201320.5.2013

2.  The importance of subject
 What is “Data Mining” ?
 Microsoft Decision Trees
 Data attributes
 Model building
 The tool ADEM
 Conslusion & Discussion

3.  Economics is the social science that analyzes the
production, distribution, and consumption of goods
and services. (Wikipedia)

4. Data mining: is the process of extracting hidden & useful information from raw data
by utilizing statistics, AI and machine learning techniques and smart algorithms.

5. Predictive Methods
1. Classification (DecisionTrees, Bayesian Classification, etc…)
2. Regression (CART, Kernel Ridge Regression etc..)
3. Artificial Neural Networks
4. Kernel Based Methods (SVM, RVM, Gaussian Processes etc...)
Descriptive Methods
1. Clustering (K-Means , Hierarchical Clustering, EM etc…)
2. Association Rules (Apriori, GRI etc..)
Decision Trees SVM ANN

6.  •Invented by MS, in 1999
•Designed for both classification and regression
•Works on both categorical & numerical attributes
•Serves entropy, Bayesian K2, and Bayesian Dirichlet
Equivalent with Uniform prior choices as splitting criteria
•Uses multi-way splits and support binary splitting
•Missing value handling is provided
•Avoids tree pruning
instead it uses complexity_penalty parameter to control the
depth of tree

7. General data
Variable name Type Usage
Day Continuous Input Day number ranging from 1 to 31
Month Continuous Input Month number ranging from 1 to 12
Day Name Discrete Input The name of the day ranging from Monday to Sunday
Is Holiday Boolean Input A flag variable (0/1) denoting that day is in weekend/holiday
or weekday
Calorie Continuous Input Total calorie amount of the menu
isMeatMenu Boolean Input Meat / Vegetarisch (True/False)
containsDessert Boolean Input Contains Dessert (True/False)
Food1 Discrete Input First food name in menu
Food2 Discrete Input Second food name in menu
Food3 Discrete Input Third food name in menu
Food4 Discrete Input Fourth food name in menu
Sales-Student-Lunch Continuous Predict Number of sales for students in lunch session
Sales-Academic-Lunch Continuous Predict Number of sales for academic staff in lunch session
Sales-Officials-Lunch Continuous Predict Number of sales for officers in lunch session

8. Overall data is 44 months period between 1.1.2008 – 21.8.2011
- 1323 records
Validation set (92)Train + Test Data (1231)
1323 records
(All data)
10 fold cross validation
for robust model selection
10 models for each
customer type (3) with 4 CP
parameter = 120 models

9. 120 different MSDT models
covering Students,Academics,Officers data
“0.4” “0.5” “0.7” and “0.85” complexity_panalty values and
VAF values are compared -> best : 0,87
 0.5 CP value and the 7th fold training data selected as the
base predictor model data
Complexity Penalty Value # of times it is winner
0.4 3
0.5 6
0.7 2
0.85 1

10.  Purely web based application
 Microsoft Analysis Services
 ASP.NET technology
 ADOMD.NET and
DMX queries
 Platform independent
Decision Tree Models
ADOMD.NET
Client
Microsoft Analysis Services
Mining
Engine
Authentication
ADEM
Online Query
Tree Explorer
Visualization
IIS 7.0 / ASP.NET 2.0

13.  Food consumption prediction is important due to balance between supply
and demand.
 Decision trees is a fine candidate for revealing food court consumption
patterns
 Multi-way splitted decision trees have model transparency which has the
model explanation power
 More data improve the results however seasonal fluctuations should be
carefully traced.
 Vegetarish selections are important on consumption amount in our case
study.
 A decision tree powered web-based decision support system is feasible and
valuable for group decision making

14.  Questions?