OpenML
cnn-stock-pred-dji

cnn-stock-pred-dji

active ARFF Publicly available Visibility: public Uploaded 28-05-2021 by Meilina Reksoprodjo
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It covers features from various categories of technical indicators, futures contracts, price of commodities, important indices of markets around the world, price of major companies in the U.S. market, and treasury bill rates. Sources and thorough description of features have been mentioned in the paper of 'CNNpred: CNN-based stock market prediction using a diverse set of variables.This dataset only contains information from the DJI.

21 features

Datestring522 unique values
0 missing
BUDAPESTnumeric217 unique values
0 missing
BARANYAnumeric114 unique values
0 missing
BACSnumeric120 unique values
0 missing
BEKESnumeric110 unique values
0 missing
BORSODnumeric160 unique values
0 missing
CSONGRADnumeric113 unique values
0 missing
FEJERnumeric110 unique values
0 missing
GYORnumeric123 unique values
0 missing
HAJDUnumeric140 unique values
0 missing
HEVESnumeric105 unique values
0 missing
JASZnumeric126 unique values
0 missing
KOMAROMnumeric86 unique values
0 missing
NOGRADnumeric82 unique values
0 missing
PESTnumeric196 unique values
0 missing
SOMOGYnumeric96 unique values
0 missing
SZABOLCSnumeric104 unique values
0 missing
TOLNAnumeric83 unique values
0 missing
VASnumeric90 unique values
0 missing
VESZPREMnumeric128 unique values
0 missing
ZALAnumeric80 unique values
0 missing

19 properties

522
Number of instances (rows) of the dataset.
21
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.
20
Number of numeric attributes.
0
Number of nominal attributes.
0.04
Number of attributes divided by the number of instances.
95.24
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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