Data
beijing_pm

beijing_pm

active ARFF CC BY 4.0 Visibility: public Uploaded 23-07-2024 by Bruno Belucci Teixeira
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
From original source: ----- This hourly data set contains the PM2.5 data of US Embassy in Beijing. Meanwhile, meteorological data from Beijing Capital International Airport are also included. Additional Information The data's time period is between Jan 1st, 2010 to Dec 31st, 2014. Missing data are denoted as "NA". Has Missing Values? Yes ----- Columns with index 0 were deleted from the dataset, usually because they related to some kind of index.

12 features

pm2.5 (target)numeric581 unique values
0 missing
yearnumeric5 unique values
0 missing
monthnumeric12 unique values
0 missing
daynumeric31 unique values
0 missing
hournumeric24 unique values
0 missing
DEWPnumeric69 unique values
0 missing
TEMPnumeric64 unique values
0 missing
PRESnumeric60 unique values
0 missing
cbwdnominal4 unique values
0 missing
Iwsnumeric2723 unique values
0 missing
Isnumeric28 unique values
0 missing
Irnumeric37 unique values
0 missing
Show all 12 features

19 properties

NumberOfInstances
41757
Number of instances (rows) of the dataset.
NumberOfFeatures
12
Number of attributes (columns) of the dataset.
NumberOfClasses
0
Number of distinct values of the target attribute (if it is nominal).
NumberOfMissingValues
0
Number of missing values in the dataset.
NumberOfInstancesWithMissingValues
0
Number of instances with at least one value missing.
NumberOfNumericFeatures
11
Number of numeric attributes.
NumberOfSymbolicFeatures
1
Number of nominal attributes.
MinorityClassPercentage
Percentage of instances belonging to the least frequent class.
MinorityClassSize
Number of instances belonging to the least frequent class.
NumberOfBinaryFeatures
0
Number of binary attributes.
PercentageOfBinaryFeatures
0
Percentage of binary attributes.
PercentageOfInstancesWithMissingValues
0
Percentage of instances having missing values.
PercentageOfMissingValues
0
Percentage of missing values.
AutoCorrelation
-11.97
Average class difference between consecutive instances.
Dimensionality
0
Number of attributes divided by the number of instances.
PercentageOfNumericFeatures
91.67
Percentage of numeric attributes.
MajorityClassPercentage
Percentage of instances belonging to the most frequent class.
PercentageOfSymbolicFeatures
8.33
Percentage of nominal attributes.
MajorityClassSize
Number of instances belonging to the most frequent class.
Show all 19 properties

1 tasks

Supervised Regression on beijing_pm
0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: pm2.5
Define a new task