Feature idea summary

Cgroups plugin supports only proportional and max Block IO policies. We should support BFQ scheduler as well. Disk stats for the scheduler are in blkio.bfq.io_service_bytes and blkio.bfq.io_serviced files.

Feature Request

Proposal:

Allow for setting "gaugesMaxTTL" option in the statsd input plugin. Essentially, this from the core statsd repo:

https://github.com/statsd/statsd/pull/599/files

Current behavior:

If deleteGauges is set to "False" then once a gauge metric is reported it is reported for the life of the telegraf server. There is no way to set a TTL value where

for reproducibility, all classifiers should be seeded by random_state. In our experiments, the random_state is set to the resampleID. This is not correctly set in all the considered classifiers. The current list to check is

all_classifiers = [
"BOSSEnsemble", "TemporalDictionaryEnsemble", "MUSE", "WEASEL",
"ProximityForest", "ElasticEnsemble", "KNeighborsTimeSeriesClassifier",
#"Shap

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提建议？
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提Feature？
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Create 2 SQL functions to manipulate strings so that all characters are converted to upper or lower case.

For example:

SELECT to_uppercase(colA), to_lowercase(colB)
FROM tab;

SELECT * 
FROM tab
WHERE to_uppercase(colA) = 'AAA';

Description

Currently, DistributionOutput classes produce a TransformedDistribution when the distribution method is invoked with loc and scale. However, we cannot get mean and variance out of such object:

import mxnet as mx
from gluonts.mx.distribution import GaussianOutput

distr_output = GaussianOutput()

args = mx.nd.array([0.0]), mx.nd.array([1.0])
loc = mx.

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually