This document discusses three machine learning techniques applied to a dataset: 1. Clustering was performed and identified 11 clusters as the "knee of the curve". 2. Classification was used to predict whether a customer wears glasses based on their 7-11 purchases. It was able to predict correctly for 9 out of 10 customers, achieving a 90% accuracy rate. 3. Association analysis was also applied but no details were provided.

1. CP463 Artificial Intelligence
WEKA PROJECT
Sirapop Kongpatyuen 55102010333

2. Data

3. Data(Con)

4. Data(Con)

5. Clustering
Knee of the curve is 11

6. Clustering(Con)
1Facewash Bread Tissue Hamburger YenYen DORM THIN NO Glass Single NO Smoke NO Alcoholic
2Pen DORM THIN NO Glass Single NO Smoke NO Alcoholic
3Candy Cookie DrinkingWater Slurpee Icecream Frozen-food DORM THIN Glass Single NO Smoke NO Alcoholic
4Facewash Prepaid Bread Tissue Ice Liquor Cigarett HOME FAT NO Glass InRelationship Smoke Alcoholic
5Pen Sausage Icecream Frozen-food DORM THIN NO Glass Single NO Smoke NO Alcoholic
6Icecream Bean Jelly Yoghurt Liquor Cigarrett HOME FAT Glass InRelationship Smoke Alcoholic
7Pen Sandwich Frozen-food DORM THIN NO Glass Single NO Smoke NO Alcoholic
8Candy Pen Cookie Sausage DrinkingWater Slurpee DORM THIN Glass Single NO Smoke NO Alcoholic
9Icecream Frozen_Food Bean Liquor HOME FAT Glass InRelationship NO Smoke Alcoholic
10Candy Cookie DrinkingWater DORM THIN NO Glass Single NO Smoke NO Alcoholic
11Facewash Prepaidcard Bread Softdrink Hamburger Liquor HOME FAT NO Glass InRelationship NO Smoke Alcoholic

7. Classification
จากการซื้อของในร้าน 7-11 เราจะทานายลักษณะของผู้ซื้อว่าใส่แว่นหรือไม่
Data

8. Classification(Con)
ทานายได้ว่า

9. Classification(Con)
ซึ่งจากข้อมูลทานายผิดไป 1 จาก 10 คือถูก 90%

10. Association