<p>&nbsp;</p>

<p><img alt="" src="https://storage.yandexcloud.net/datasouls-ods/images/2020/04/17/559b2323-c538-44ad-9fa8-f644efa72006/tp.png" /></p>

<p>Competition of the classification algorithms of wild fires according to the data of temperature anomalies from satellites.</p>

<h2>Problem Statement</h2>

<p>It is necessary to classify the type of a wild fire (according to the Ministry of Emergency Situations classification) based on the information about the point of temperature anomaly. The solution should be implemented in the form of a program, which takes a CSV table with points as input (latitude and longitude coordinates, and the date when the point was received). It is necessary to make a table with probabilities for each of 11 classes (columns fire_1_prob, fire_11_prob) as output.</p>

<h2>Evaluation</h2>

<p>The solution represents an archive with a code, which is launched in the Docker container environment. The solutions validation occurs at new points coming from an automatized system. The quality of the solution is evaluated by a set of points for a certain predetermined period of time. Quality metric &mdash; Micro-averaged Multi-Class ROC-AUC counted for all types of wild fires (11 classes).</p>

<h2>Prizes</h2>

<p>Total prize pool is 700 000 RUB. The winning team will receive 300,000 RUB, the second place team will receive 200,000 RUB, the team placing the third will receive 100,000 RUB. In addition, the best public decision published on github will receive an additional jury prize of 100,000 RUB.</p>

Develop an algorithm for classifying forest fires in the points of temperature anomalies

Private

https://storage.yandexcloud.net/ds-ods/files/media/meta_tag/file/3fed2fb41913/badge.jpg

Develop an algorithm for classifying forest fires according to the points of temperature anomalies.

description

Wildfire AI: Classification of Fire Reasons

Container

Gardeners

plotnikov.ilia938

RaevskyDN

yuzhou

Orcs

Литр сибаса [DataGym]

1/2push

journeil06

Mamat Shamshiev MMP MSU

ЗдесьМоглаБытьВашаРеклама

aborisihin

rurostok

brs1977

algolib

fedotov.dimka

[La] BlackFriday

princess tiabenie

Tri Pelmenya

ahtoh874

artas

polosataya

vanpnkv

Slava Bakulin

MESS TEAM

exotol

Lagransh

anpolvk

ПушистыйХвостСтальныеЛапы

Hunter

Vlad Samarov

darayavaus

vladimirwest

nikitaminaev

andygoosh

Alexey Pismenny MMP MSU

kovrigindanila

anatoly

🔥 

bora007

Best

Sergey Zlobin

Pavel Tikhonov

capitan

nastiyona

¯\_(ツ)_/¯

SARRACENIA

СушитеВеслаСибирьГорит

Score

#	Teams (79)	Score	Last	Entries
1	Gardeners	0.9248576505	7y	74
2	plotnikov.ilia938	0.9246797864	7y	29
3	RaevskyDN	0.9246271037	7y	47
4	yuzhou	0.9214127907	7y	19
5	Orcs	0.9205778844	7y	38
6	Литр сибаса [DataGym]	0.9203706979	7y	19
7	1/2push	0.9202168412	7y	5
8	journeil06	0.9198458626	7y	6
9	Mamat Shamshiev MMP MSU	0.9184341788	7y	6
10	ЗдесьМоглаБытьВашаРеклама	0.9172184921	7y	42
11	emm	0.9169983856	7y	18
12	aborisihin	0.9163543783	7y	24
13	rurostok	0.9162300362	7y	15
14	OK	0.9150345602	7y	39
15	brs1977	0.9146821867	7y	3
16	algolib	0.9129847809	7y	6
17	fedotov.dimka	0.9129847809	7y	32
18	[La] BlackFriday	0.9128754982	7y	10
19	princess tiabenie	0.9127049592	7y	5
20	s	0.9119583415	7y	6
21	Tri Pelmenya	0.9118347614	7y	9
22	ahtoh874	0.9117763806	7y	4
23	artas	0.9114831569	7y	16
24	polosataya	0.9113123568	7y	24
25	vanpnkv	0.910534405	7y	4
26	Slava Bakulin	0.9098761332	7y	38
27	MESS TEAM	0.9096692451	7y	42
28	exotol	0.9095381489	7y	79
29	Lagransh	0.9090307277	7y	14
30	anpolvk	0.9090227352	7y	3
31	ПушистыйХвостСтальныеЛапы	0.9084585404	7y	5
32	Hunter	0.9078638939	7y	23
33	Vlad Samarov	0.9074252278	7y	124
34	darayavaus	0.9060654863	7y	50
35	vladimirwest	0.9055647446	7y	1
36	nikitaminaev	0.9047895061	7y	12
37	andygoosh	0.9034887351	7y	20
38	Alexey Pismenny MMP MSU	0.9032864631	7y	23
39	kovrigindanila	0.8995710511	7y	23
40	anatoly	0.8925691617	7y	18
41	🔥	0.8912167052	7y	31
42	bora007	0.8882313994	7y	13
43	Best	0.8823714768	7y	40
44	Sergey Zlobin	0.8777259725	7y	17
45	Pavel Tikhonov	0.8698318134	7y	3
46	capitan	0.8674073907	7y	14
47	nastiyona	0.8655935392	7y	4
48	¯\_(ツ)_/¯	0.8649604486	7y	21
49	SARRACENIA	0.8600696895	7y	18
50	СушитеВеслаСибирьГорит	0.8591375983	7y	4