Basic use of RapidMiner (a simple decision tree algorithm analysis of a medical data)

<title>Basic use of RapidMiner (a simple decision tree algorithm analysis of a medical data)</title> Basic use of RapidMiner (a simple decision tree algorithm analysis of a medical data)

Files that need to be analyzed:

Right-click to create a few processes that read Excel data, select Properties, set objects, decision tree algorithms, and then connect them
Read Excel data: "Insert Operator", "Import", "Data", "read Excel"
Select Properties: "Insert Operator", "Data Transformation", "Attribute Set Reduction and Transformation", "Selection"- > "Select Attributes"
Set object: "Insert Operator", "Data Transformation", "Name and Role Modification", "Set Role"
Decision Tree algorithm: "Insert Operator", "Modeling", "Classification and Regression", "Tree induction", "Decision tree"

Click on the "Read Excel" procedure and the right appears

Click on "Import Configuration Wizard"

Full gray indicates all selected, click "Next"

The name of the first column indicates that the first column is not data, and if you do not fill it, the first column is the same as the following data type, "Next"

Weight change is only two values, select "Binominal". Click "Finish"

Click "Attribute filter Type" In the "select Attributes" procedure to select "All" to analyze all columns

Click on "Weight Change" in "attribute name" in "Set role", "label" in "Target role", the main object of weight change

Decision tree algorithm by default,

Click Run

Building a decision Tree

1.Tree
2.Indicators 1 > 5.883
3.|Indicators 2 > 9.843: negative {negative = 2, positive = 0}
4. |indicator 2≤9.843
5. |   |Indicators 3 > 9.868: negative {negative = 2, positive = 1}
6. |   |indicator 3≤9.868
7. |   |   |Indicators 2 > 8.645
8. |   |   |   |Indicators 3 > 6.614: negative {negative = 7, positive = 0}
9. |   |   |   |indicator 3≤6.614
. |   |   |   |   |Indicators 1 > 6.736: positive {negative = 0, positive = 11}
  one by one.|   |   |   |   |Indicator 1≤6.736: Negative {negative = 1, positive = 1}
. |   |   |indicator 2≤8.645: positive {negative = 8, positive = 182}
 Indicator 1≤5.883
. |Indicators 3 > 0.027
A . |   |Indicators 3 > 0.234
. |   |   |Indicators 2 > 5.642: negative {negative = 110, positive = 0}
. |   |   |indicator 2≤5.642
. |   |   |   |Indicators 1 > 3.079
. |   |   |   |   |Indicators 3 > 8.448: negative {negative = 11, positive = 0}
. |   |   |   |   |indicator 3≤8.448
. |   |   |   |   |   |Indicators 5 > 0.370
. |   |   |   |   |   |   |Indicators 3 > 3.320
. |   |   |   |   |   |   |   |Indicators 4 > 0.559
A . |   |   |   |   |   |   |   |   |Indicators 1 > 3.369
. |   |   |   |   |   |   |   |   |   |Indicators 3 > 5.871
. |   |   |   |   |   |   |   |   |   |   |Indicators 2 > 1.889
. |   |   |   |   |   |   |   |   |   |   |   |Indicators 1 > 5.517: positive {negative = 0, positive = 2}
. |   |   |   |   |   |   |   |   |   |   |   |Indicator 1≤5.517
. |   |   |   |   |   |   |   |   |   |   |   |   |Indicators 5 > 8.864: positive {negative = 0, positive = 2}
. |   |   |   |   |   |   |   |   |   |   |   |   |Indicator 5≤8.864: negative {negative = 12, positive = 0}
. |   |   |   |   |   |   |   |   |   |   |indicator 2≤1.889: positive {negative = 0, positive = 6}
. |   |   |   |   |   |   |   |   |   |indicator 3≤5.871: positive {negative = 0, positive = 15}
. |   |   |   |   |   |   |   |   |indicator 1≤3.369: negative {negative = 3, positive = 0}
. |   |   |   |   |   |   |   |indicator 4≤0.559: negative {negative = 4, positive = 0}
. |   |   |   |   |   |   |indicator 3≤3.320: positive {negative = 0, positive = 24}
. |   |   |   |   |   |indicator 5≤0.370: negative {negative = 2, positive = 0}
The PNs. |   |   |   |indicator 1≤3.079
. |   |   |   |   |Indicators 2 > 0.268
. |   |   |   |   |   |Indicators 3 > 1.365: Negative {positive = 1, negative = 64}
. |   |   |   |   |   |indicator 3≤1.365
. |   |   |   |   |   |   |Indicators 2 > 1.977
A . |   |   |   |   |   |   |   |Indicators 1 > 1.829: positive {negative = 1, positive = 3}
. |   |   |   |   |   |   |   |indicator 1≤1.829: negative {negative = 7, positive = 0}
. |   |   |   |   |   |   |indicator 2≤1.977: positive {negative = 0, positive = 2}
. |   |   |   |   |indicator 2≤0.268
. |   |   |   |   |   |Indicators 1 > 1.251: positive {negative = 0, positive = 3}
. |   |   |   |   |   |indicator 1≤1.251: negative {negative = 2, positive = 0}
. |   |indicator 3≤0.234
. |   |   |Indicators 1 > 2.099: positive {negative = 0, positive = 7}
. |   |   |indicator 1≤2.099: negative {negative = 2, positive = 0}
. |indicator 3≤0.027: positive {negative = 0, positive =2}

Also, right-click on the table data read process and select "Show exampleset Result"

Data statistical analysis available

Basic use of RapidMiner (a simple decision tree algorithm analysis of a medical data)