Summary

Today in the R package, there are a lot of internal function calls which use only positional arguments. Change them to use keyword arguments for extra safety.

I've added this issue to provide a small, focused contribution opportunity for Hacktoberfest 2020 participants. If you are an experienced open source contributor, please leave this

Not a high-priority at all, but it'd be more sensible for such a tutorial/testing utility corpus to be implemented elsewhere - maybe under /test/ or some other data- or doc- related module – rather than in gensim.models.word2vec.

Originally posted by @gojomo in RaRe-Technologies/gensim#2939 (comment)

Problem:
catboost version: 0.23.2
Operating System: all
Tutorial: https://github.com/catboost/tutorials/blob/master/custom_loss/custom_metric_tutorial.md

Impossible to use custom metric (С++).

Code example

from catboost import CatBoost
train_data = [[1, 4, 5, 6],
 

Describe the bug
Filtering with the =~ operator doesn't work

To Reproduce

LET doc = DOCUMENT("https://www.amazon.de/gp/product/B0172JEA7K")
LET meta = ELEMENT(doc, '[data-automation-id="meta-info"]')

FOR a IN ELEMENTS(meta, 'a')
	FILTER a.attributes.href =~ "atv_dp_pd_star"
	RETURN TRIM(a.innerHTML)

returns

{
    "error": "compile query: invalid token: FIL

I'm using latest pyod version on pypi. How to generate simulated data where x-axis is time? Thank you.

We currently support the following strategies for reduction from forecasting to regression:

• direct
• recursive
• dirrec (see #226)

Some models can directly predict multiple outputs, see e.g. LinearRegression:

import numpy as np
from sklearn.linear_model import LinearRegression

y = np.random.normal(size=(10, 3))
X = np.random.normal(size=(10, 5))

estimator = LinearRegr