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HarHarLinks
HarHarLinks commented May 22, 2022

Steps to reproduce

image

Outcome

What did you expect?

at least use the available vertical space

Operating system

arch

Application version

Element Nightly version: 2022052102 Olm version: 3.2.8

How did you install the app?

aur

Homeserver

1.59.1

Wil

T-Defect S-Minor A-DevTools O-Uncommon
NicolasHug
NicolasHug commented Apr 6, 2018

For now only strings are accepted as the measures parameter in GridSearchCV, RandomizedSearchCV, and cross_validate. It's thus impossible to use those with measures that take specific parameters as input (e.g. #156 ), or to use custom measures.

We should then accept callables in addition to strings.

Each callable should only take the predictions parameter. In order to handle measur

bridge between mattermost, IRC, gitter, xmpp, slack, discord, telegram, rocketchat, twitch, ssh-chat, zulip, whatsapp, keybase, matrix, microsoft teams, nextcloud, mumble, vk and more with REST API (mattermost not required!)

  • Updated May 21, 2022
  • Go
dendrite
cfunky
cfunky commented Mar 1, 2022

I noticed that CooMatrix::push_matrix does not threshold or detect zero elements in the input. Thus the resulting sparse matrix is more dense than it needs to be. By comparison, constructing a matrix using, e.g., CscMatrix::from, does detect entries that are exactly zero and does not include them in the resulting sparse matrix. If there isn't a rationale for the difference in behavior, may I s

good first issue documentation nalgebra-sparse
HarHarLinks
HarHarLinks commented Jan 22, 2022

Steps to reproduce

  1. disable emoji kb in settings
  2. open room
  3. compose normally: no emoji kb button
  4. swipe a message to start a reply
  5. there is now a button to switch kb, partially in broken state

Outcome

see above

Your phone model

No response

Operating system version

No response

Application version and app store

1.3.15 F-Droid

Homeserver

_No resp

T-Defect good first issue A-Composer Z-Papercuts
Linear_Algebra_With_Python

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the most must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.

  • Updated Mar 23, 2022
  • Jupyter Notebook

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