How to classify test objects with this ruleset in order of priority? I'm coding a program that tests several classifiers over a database weather.arff, I found rules below, I want classify test objects.

I do not understand how the classification, it is described:
"In classification, let R be the set of generated rules and T the training data. The basic idea of the proposed method is to choose a set of high confidence rules in R to cover T. In classifying a test object, the first rule in the set of rules that matches the test object condition classifies it. This process ensures that only the highest ranked rules classify test objects. "

How to classify test objects?

No. outlook temperature humidity    windy   play
1   sunny       hot     high        FALSE   no
2   sunny       hot     high        TRUE    no
3   overcast    hot     high        FALSE   yes
4   rainy       mild    high        FALSE   yes
5   rainy       cool    normal      FALSE   yes
6   rainy       cool    normal      TRUE    no
7   overcast    cool    normal      TRUE    yes
8   sunny       mild    high        FALSE   no
9   sunny       cool    normal      FALSE   yes
10  rainy       mild    normal      FALSE   yes
11  sunny       mild    normal      TRUE    yes
12  overcast    mild    high        TRUE    yes
13  overcast    hot     normal      FALSE   yes
14  rainy       mild    high        TRUE    no


Rule found:

1: (outlook,overcast) -&gt; (play,yes) 
[Support=0.29 , Confidence=1.00 , Correctly Classify= 3, 7, 12, 13]

2: (humidity,normal), (windy,FALSE) -&gt; (play,yes)
[Support=0.29 , Confidence=1.00 , Correctly Classify= 5, 9, 10]

3: (outlook,sunny), (humidity,high) -&gt; (play,no) 
[Support=0.21 , Confidence=1.00 , Correctly Classify= 1, 2, 8]

4: (outlook,rainy), (windy,FALSE) -&gt; (play,yes) 
[Support=0.21 , Confidence=1.00 , Correctly Classify= 4]

5: (outlook,sunny), (humidity,normal) -&gt; (play,yes) 
[Support=0.14 , Confidence=1.00 , Correctly Classify= 11]

6: (outlook,rainy), (windy,TRUE) -&gt; (play,no) 
[Support=0.14 , Confidence=1.00 , Correctly Classify= 6, 14]


Thanks,
Dung
Suppose your test object is (sunny, hot, normal, TRUE). Look through the rules top to bottom and see if any of the conditions are matched. The first rule for example tests the outlook feature. The value doesn't match, so the rule isn't matched. Move on to the next rule. And so on. In this case, rule 5 matches the test case and the classification for the p lay variable is "yes".

More generally, for any test case, look at the values its features take and find the first rule that those values satisfy. The implication of that rule will be its classification.