hanaml.ROCKET.Rd
RandOm Convolutional KErnel Transform (ROCKET) is an exceptionally efficient algorithm for time series classification. Unlike other proposed time series classification algorithms which attain excellent accuracy, ROCKET maintains its performance with a fraction of the computational expense by transforming input time series using random convolutional kernels.
hanaml.ROCKET(
data = NULL,
key = NULL,
method = NULL,
num.features = NULL,
data.dim = NULL,
random.seed = NULL
)
DataFrame
Specifies the input time-series data.
character, optional
Specifies the column name in data
that represents the order of time-series.
character, optional
The options are "MiniRocket" and "MultiRocket".
Defaults to "MiniRocket".
integer, optional
Number of transformed features for each time series.
Defaults to 9996 when method = "MiniRocket", 49728 when method is "MultiRocket".
integer, optional
Dimensionality of the multivariate time series.
1 means univariate time series and others for multivariate. Cannot be smaller than 1.
Defaults to 1.
integer, optional
0 indicates using machine time as seed.
Defaults to 0.
A "ROCKET" object with the following attribute:
model : DataFrame
Trained model content.
Input time-series data:
> data$Collect()
RECORD_ID VAL_1 VAL_2 VAL_3 VAL_4 VAL_5 VAL_6 ... VAL_10 VAL_11 VAL_12 VAL_13 VAL_14 VAL_15 VAL_16
0 0 1.598 1.599 1.571 1.550 1.507 1.434 ... 1.117 1.024 0.926 0.828 0.739 0.643 0.556
1 1 1.701 1.671 1.619 1.547 1.475 1.391 ... 1.070 0.985 0.899 0.816 0.733 0.658 0.581
2 2 1.722 1.695 1.657 1.606 1.512 1.414 ... 1.015 0.920 0.828 0.740 0.658 0.586 0.501
3 3 1.726 1.660 1.573 1.496 1.409 1.332 ... 0.987 0.901 0.815 0.730 0.644 0.558 0.484
4 4 1.779 1.761 1.703 1.611 1.492 1.369 ... 0.900 0.786 0.679 0.580 0.502 0.415 0.333
5 5 1.800 1.743 1.686 1.633 1.532 1.423 ... 0.979 0.872 0.767 0.664 0.561 0.453 0.355
6 6 1.749 1.727 1.659 1.560 1.457 1.355 ... 0.961 0.864 0.771 0.682 0.595 0.513 0.427
7 7 1.348 1.237 1.129 1.022 0.939 0.847 ... 0.474 0.388 0.306 0.218 0.133 0.061 0.009
8 8 1.696 1.634 1.596 1.507 1.414 1.323 ... 1.048 0.966 0.890 0.805 0.719 0.632 0.553
9 9 1.723 1.713 1.665 1.587 1.495 1.404 ... 1.041 0.955 0.870 0.787 0.706 0.622 0.547
10 10 1.614 1.574 1.557 1.521 1.460 1.406 ... 1.045 0.957 0.862 0.771 0.681 0.587 0.497
11 11 1.652 1.665 1.656 1.623 1.571 1.499 ... 1.155 1.058 0.973 0.877 0.797 0.704 0.609
Invoke hanaml.ROCKET:
> ro <- hanaml.ROCKET(data = df, key = 'RECORD_ID', method = "MiniRocket", random.seed = 1)
> ro$model$Collect()
MODEL_CONTENT
0 -1 MultiRocket
1 0 {"SERIES_LENGTH":16,"NUM_CHANNELS":8,"BIAS_SIZ...
2 1 HANNELS":[6]},{"ID":77,"CHANNELS":[1,4,7,6,5]}...
3 2 340878522815215,7.959895076819708,5.8147048859...
......