ํ์ด์ฌ์ผ๋ก ๊ธฐ์ด์ ์ธ ํ๋ก๊ทธ๋จ์ ํ๋ก๊ทธ๋๋ฐ ํ๋ค ๋ณด๋ฉด, ์ค๋ฅ๋ฅผ ํธ๋ค๋ง ํด์ผ ํ๋ ๊ฒฝ์ฐ๊ฐ ๋ง์ต๋๋ค. When user enters invalid input, it is common to abort the program. ๊ทธ๋ ๊ฒ ํ๊ธฐ ์ํด์๋, sys standard library module์ ์ ์๋ exit ํจ์๋ฅผ ์ฌ์ฉํ๋ฉด ๋ฉ๋๋ค. from sys import exitif not (userResponse == "n" or userResponse == "y"): exit("Error: you must enter either n or y.") exit(errorMessage) ํ์์ผ๋ก ํ๋ก๊ทธ๋จ terminate ์์ ์ถ๋ ฅ๋ ์๋ฌ ๋ฉ์์ง๋ฅผ ์ธ์๋ก ๋ฃ์ผ๋ฉด ๋ฉ๋๋ค.
There are some ways in Python to analyze string. substring in sReturns True if the string s contains substring and False otherwise.if "-" is not in name: ...s.count(substring)Returns the number of non-overlapping occurrences of substring in s.s.endswith(substring)Returns True if the string s ends with the substring and False otherwise.s.startswith(substring)Returns True if the string s starts w..
There are two types of predictions in data science. Regression์ numerical data๋ฅผ ์์ธกํ๋๋ฐ ์ฌ์ฉํ๊ณ , Classification ์ cateogorical data๋ฅผ ์์ธกํ๋๋ฐ ์ฌ์ฉํฉ๋๋ค. ์๋ฅผ ๋ค์ด, ์ฐ๋ฆฌ๊ฐ ์ฌ์ฉํ๋ ์ด๋ฉ์ผ์ ์คํธ ๋ฉ์ผํจ์ด ์์ต๋๋ค.๋ฉ์ผ์ ํ
์คํธ ๋ฐ์ดํฐ๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ์คํธ์ธ์ง ์๋์ง, Yes or No ์ ํด๋นํ๋ Cateogorical variable์ ์์ธกํฉ๋๋ค. Input = Text / Output = Yes or No (Spam, Not Spam) Classification์ ๋ํด์ ๋ ์์ธํ ์์๋ณด๊ธฐ ์ด์ , ๊ฐ๋จํ๊ฒ Machine Learning์ ๋ํด์ ์์๋ณด๊ฒ ์ต๋๋ค. Machine Learning Algorit..
In a simple linear regression line (LMS), the regression line can be expressed as following equation:y = ax + bwherey = The variable that you want to predict (์์ธกํ๊ณ ์ถ์ ๊ฐ) | Dependent variable (์ข
์ ๋ณ์)x = The variable that you are using to predict (์์ธก์ ์ฌ์ฉํ๋ ๊ฐ) | Independent variable (๋
๋ฆฝ ๋ณ์)a = Slope (๊ธฐ์ธ๊ธฐ)b = y-intercept (y ์ ํธ) ๊ทธ๋ ๋ค๋ฉด, y = ax+b ์์ slope(a)์ y-intercept(b)๋ ์ด๋ป๊ฒ ๊ตฌํ๋์ง ์์๋ณด๊ฒ ์ต๋๋ค. Recall, r ..