OpenML
post-operative

post-operative

active ARFF Publicly available Visibility: public Uploaded 11-06-2021 by Meilina Reksoprodjo
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Author: Sharon Summers Source: [UCI](https://archive.ics.uci.edu/ml/datasets/Post-Operative+Patient) - 1993 Please cite: [UCI](https://archive.ics.uci.edu/ml/citation_policy.html) Post-Operative Patient Data Set The classification task of this database is to determine where patients in a postoperative recovery area should be sent to next. Because hypothermia is a significant concern after surgery (Woolery, L. et. al. 1991), the attributes correspond roughly to body temperature measurements. ### Attribute information 1. L-CORE (patient's internal temperature in C): high (> 37), mid (>= 36 and <= 37), low (< 36) 2. L-SURF (patient's surface temperature in C): high (> 36.5), mid (>= 36.5 and <= 35), low (< 35) 3. L-O2 (oxygen saturation in %): excellent (>= 98), good (>= 90 and < 98), fair (>= 80 and < 90), poor (< 80) 4. L-BP (last measurement of blood pressure): high (> 130/90), mid (<= 130/90 and >= 90/70), low (< 90/70) 5. SURF-STBL (stability of patient's surface temperature): stable, mod-stable, unstable 6. CORE-STBL (stability of patient's core temperature) stable, mod-stable, unstable 7. BP-STBL (stability of patient's blood pressure) stable, mod-stable, unstable 8. COMFORT (patient's perceived comfort at discharge, measured as an integer between 0 and 20) 9. decision ADM-DECS (discharge decision): I (patient sent to Intensive Care Unit), S (patient prepared to go home), A (patient sent to general hospital floor)

12 features

Source Portnumeric22724 unique values
0 missing
Destination Portnumeric3273 unique values
0 missing
NAT Source Portnumeric29152 unique values
0 missing
NAT Destination Portnumeric2533 unique values
0 missing
Actionstring4 unique values
0 missing
Bytesnumeric10724 unique values
0 missing
Bytes Sentnumeric6683 unique values
0 missing
Bytes Receivednumeric8814 unique values
0 missing
Packetsnumeric1116 unique values
0 missing
Elapsed Time (sec)numeric915 unique values
0 missing
pkts_sentnumeric749 unique values
0 missing
pkts_receivednumeric922 unique values
0 missing

19 properties

65532
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
11
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
91.67
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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