We will again use the examples from Chapter 2, Naive Bayes, and Chapter 3, Decision Tree, as follows:
Temperature |
Wind |
Sunshine |
Play |
Cold |
Strong |
Cloudy |
No |
Warm |
Strong |
Cloudy |
No |
Warm |
None |
Sunny |
Yes |
Hot |
None |
Sunny |
No |
Hot |
Breeze |
Cloudy |
Yes |
Warm |
Breeze |
Sunny |
Yes |
Cold |
Breeze |
Cloudy |
No |
Cold |
None |
Sunny |
Yes |
Hot |
Strong |
Cloudy |
Yes |
Warm |
None |
Cloudy |
Yes |
Warm |
Strong |
Sunny |
? |
Â
However, we would like to use a random forest consisting of four random decision trees to find the result of the classification.