Data Visualization Report in Weka
Submitted By:
Dawood Faiz
Submitted To:
Mr. Asif
Subject:
Machine Learning
Date: 20-10-2020
NATIONAL COLLEGE OF BUSINESS ADMINISTRATION & ECONOMICS
(NCBA&E) Wapda Town Campus Multan
Dataset Background
The dataset being used in this report is related to “Heart Failure Prediction”. This dataset
comprises of 12 clinical features for prediction of mortality caused by heart failure. These
features are:
1) “age” with minimum value of 40 and maximum value of 95.
2) “anaemia" with minimum Boolean value of 0 and maximum value of 1.
3) “creatinine_phosphokinase” with minimum value of 23 and maximum value of 7861
(mcg/L).
4) “diabetes” with minimum Boolean value of 0 and maximum value of 1.
5) “ejection_fraction” with minimum value of 14% and maximum value of 80%.
6) “high_blood_pressure” with minimum Boolean value of 0 and maximum value of 1.
7) “platelets” with minimum value of 25.1k and maximum value of 850k (kiloplatelets/mL).
8) “serum_creatinine” with minimum value of 0.5 and maximum value of 9.4 (mg/dL).
9) “serum_sodium” with minimum value of 113 and maximum value of 148 (mEq/L).
10) “sex” with minimum binary value of 0 and maximum value of 1.
11) “smoking” with minimum Boolean value of 0 and maximum value of 1.
12) “time” with minimum value of 4 and maximum value of 285 days.
Preprocessing in Weka
The “Preprocess” tab of Weka shows different panels of the data set. The current relation panel
shows all the attributes (number of columns) included in CSV file which in this case are 13 as
well as the number of instances (number of rows) in CSV file which in this case are 299. This
panel also shows the relation (dataset name) of opened CSV file which in this case is
“heart_failure_clinical_records_dataset”.
All attributes can be visualized at once as well.
Dataset Visualization in Weka