Forecast by nandiya · Pull Request #3219 · TheAlgorithms/Python

nandiya · 2020-10-12T06:10:00Z

Describe your change:

Add an algorithm?
Fix a bug or typo in an existing algorithm?
Documentation change?

Checklist:

nandiya · 2020-10-12T06:17:39Z

@dhruvmanila please review my code

cclauss · 2020-10-12T20:09:45Z

machine_learning/forecasting/run.py

+from statsmodels.tsa.statespace.sarimax import SARIMAX
+
+
+def lin_reg_pred(train_dt, train_usr, train_mtch, test_dt, test_mtch):


Type hints? Doctests? See CONTRIBUTING.md.

TravisBuddy · 2020-10-13T02:41:01Z

Travis tests have failed

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TravisBuddy Request Identifier: 85c68050-0cfd-11eb-b943-5b98ff54aa42

TravisBuddy · 2020-10-13T02:45:04Z

Travis tests have failed

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TravisBuddy Request Identifier: 16dd23f0-0cfe-11eb-b943-5b98ff54aa42

machine_learning/forecasting/run.py

TravisBuddy · 2020-10-13T10:11:47Z

Travis tests have failed

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cclauss · 2020-10-13T10:12:05Z

machine_learning/forecasting/run.py

+    return prediction
+
+
+def sarimax_predictor(train_user, train_match, test_match):


Type hints?

cclauss · 2020-10-13T10:12:16Z

machine_learning/forecasting/run.py

+    return result[0]
+
+
+def support_machine_regressor(x_train, x_test, train_user):


Type hints?

cclauss · 2020-10-13T10:12:26Z

machine_learning/forecasting/run.py

+    return y_pred[0]
+
+
+def interquartile_range_checker(train_user):


Type hints?

cclauss · 2020-10-13T10:12:41Z

machine_learning/forecasting/run.py

+    return low_lim
+
+
+def data_safety_checker(list_vote, actual_result):


Type hints?

arent the hints input and output that i described??
or did i do it wrongly?

https://docs.python.org/3/library/typing.html is described in CONTRIBUTING.md. Or look at other Python files in this repo.

cclauss · 2020-10-13T10:15:55Z

machine_learning/forecasting/run.py

+
+
+# data_input_df = pd.read_csv("ex_data.csv", header=None)
+list_data = [[18231, 0.0, 1], [22621, 1.0, 2], [15675, 0.0, 3], [23583, 1.0, 4]]


Please provide a more self-documenting variable name than list_data. What is this a list of? Are these stock quotes or swine flu patients or food orders? Help the reader understand what this data is so they can understand why all this analysis is worth doing.

done, please check it if the current one can be used or not

TravisBuddy · 2020-10-13T10:17:53Z

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TravisBuddy · 2020-10-13T10:21:47Z

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TravisBuddy · 2020-10-13T12:40:53Z

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TravisBuddy · 2020-10-13T12:48:25Z

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nandiya · 2020-10-13T13:01:43Z

@cclauss i'm still confuse with the hints that u were mentioned, since in contributing.md only described normal input and output

cclauss · 2020-10-24T09:22:38Z

From CONTRIBUTING.md:

The use of Python type hints is encouraged for function parameters and return values. Our automated testing will run mypy so run that locally before making your submission.

def sum_ab(a: int, b: int) -> int:
    return a + b

nandiya · 2020-10-24T10:01:05Z

@cclauss done changing that
but please help me one thing, i think the web https://gitlab.com/pycqa/flake8 is down, so its unable to use flake resulting unpass pre commit.. please do something abt it.

cclauss

Type hints on data_safety_checker() please.

cclauss · 2020-10-24T13:14:11Z

machine_learning/forecasting/run.py

+from statsmodels.tsa.statespace.sarimax import SARIMAX
+
+
+def lin_reg_pred(


Suggested change

def lin_reg_pred(

def linear regression_prediction(

Don't make the reader guess.

cclauss · 2020-10-24T13:14:51Z

machine_learning/forecasting/run.py

+    prediction = abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])
+    return prediction


Suggested change

prediction = abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])

return prediction

return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])

cclauss · 2020-10-24T13:15:58Z

machine_learning/forecasting/run.py

+    return result[0]
+
+
+def support_machine_regressor(x_train: list, x_test: list, train_user: list) -> float:


Suggested change

def support_machine_regressor(x_train: list, x_test: list, train_user: list) -> float:

def support_vector_regressor(x_train: list, x_test: list, train_user: list) -> float:

Matches the docstring on the next line.

cclauss · 2020-10-24T13:18:47Z

machine_learning/forecasting/run.py

+    if safe > not_safe:
+        print("today's data is safe")
+    else:
+        print("today's data is not safe")


Suggested change

if safe > not_safe:

print("today's data is safe")

else:

print("today's data is not safe")

print("today's data is {'not ' if safe <= not_safe else ''}safe")

idk whether that code is working, but i got ur point to use inline if print

--done

cclauss

Thanks for your persistence!

* add forecasting code * add statsmodel * sort import * sort import fix * fixing black * sort requirement * optimize code * try with limited data * sort again * sort fix * sort fix * delete warning and black * add code for forecasting * use black * add more hints to describe * add doctest * finding whitespace * fixing doctest * delete * revert back * revert back * revert back again * revert back again * revert back again * try trimming whitespace * try adding doctypeand etc * fixing reviews * deleting all the space * fixing the build * delete x * add description for safety checker * deleting subscription integer * fix docthint * make def to use function parameters and return values * make def to use function parameters and return values * type hints on data safety checker * optimize code * Update run.py Co-authored-by: FVFYK3GEHV22 <fvfyk3gehv22@FVFYK3GEHV22s-MacBook-Pro.local> Co-authored-by: Christian Clauss <cclauss@me.com>

FVFYK3GEHV22 added 15 commits October 12, 2020 11:31

add forecasting code

722584e

add statsmodel

0b823da

sort import

aab3a71

sort import fix

8f69418

fixing black

31b8926

sort requirement

e3ba4fa

optimize code

058889b

try with limited data

7a58104

sort again

6f0b775

sort fix

5fd4b05

sort fix

4864b41

delete warning and black

122fdc6

resolve error merge

4785ddf

add code for forecasting

b3df925

use black

cfa6a2f

cclauss requested changes Oct 12, 2020

View reviewed changes

FVFYK3GEHV22 added 3 commits October 13, 2020 09:22

add more hints to describe

cefc5f4

add doctest

85b37cc

finding whitespace

13d23b6

FVFYK3GEHV22 added 8 commits October 13, 2020 09:59

fixing doctest

aa0daa5

delete

1e6f923

revert back

ab98e75

revert back

3851388

revert back again

6fb8a22

Merge branch 'forecast' of github.com:nandiya/Python into forecast

89e60a8

revert back again

574d25d

revert back again

c151dd5

deleting all the space

14ccdc8

cclauss reviewed Oct 13, 2020

View reviewed changes

machine_learning/forecasting/run.py Outdated Show resolved Hide resolved

fixing the build

8194902

delete x

eab1d3b

cclauss requested changes Oct 13, 2020

View reviewed changes

add description for safety checker

d34853f

deleting subscription integer

81effc5

fix docthint

6c8f1af

kbakdev approved these changes Oct 22, 2020

View reviewed changes

make def to use function parameters and return values

070cba4

make def to use function parameters and return values

28ac649

cclauss requested changes Oct 24, 2020

View reviewed changes

FVFYK3GEHV22 and others added 3 commits October 24, 2020 20:42

type hints on data safety checker

da69f83

optimize code

3b18a48

Update run.py

85723b6

nandiya requested a review from cclauss October 24, 2020 14:04

cclauss approved these changes Oct 24, 2020

View reviewed changes

cclauss merged commit 12c6980 into TheAlgorithms:master Oct 24, 2020

		from statsmodels.tsa.statespace.sarimax import SARIMAX


		def lin_reg_pred(train_dt, train_usr, train_mtch, test_dt, test_mtch):

		return prediction


		def sarimax_predictor(train_user, train_match, test_match):

		return result[0]


		def support_machine_regressor(x_train, x_test, train_user):

		return y_pred[0]


		def interquartile_range_checker(train_user):

		return low_lim


		def data_safety_checker(list_vote, actual_result):



		# data_input_df = pd.read_csv("ex_data.csv", header=None)
		list_data = [[18231, 0.0, 1], [22621, 1.0, 2], [15675, 0.0, 3], [23583, 1.0, 4]]

		from statsmodels.tsa.statespace.sarimax import SARIMAX


		def lin_reg_pred(

		prediction = abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])
		return prediction

	prediction = abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])
	return prediction
	return abs(beta[0] + test_dt[0] * beta[1] + test_mtch[0] + beta[2])

		return result[0]


		def support_machine_regressor(x_train: list, x_test: list, train_user: list) -> float:

	def support_machine_regressor(x_train: list, x_test: list, train_user: list) -> float:
	def support_vector_regressor(x_train: list, x_test: list, train_user: list) -> float:

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nandiya commented Oct 12, 2020

Describe your change:

Checklist:

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TravisBuddy commented Oct 13, 2020

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TravisBuddy Request Identifier: 85c68050-0cfd-11eb-b943-5b98ff54aa42

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TravisBuddy commented Oct 13, 2020

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TravisBuddy commented Oct 13, 2020

Travis tests have failed

TravisBuddy Request Identifier: 58799020-0d3d-11eb-9111-f326d0cb7f09

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TravisBuddy commented Oct 13, 2020

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TravisBuddy commented Oct 13, 2020

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TravisBuddy commented Oct 13, 2020

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nandiya commented Oct 13, 2020

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cclauss commented Oct 24, 2020

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