분류 전체보기
-
Multiple Linear regressionMLAI/Regression 2020. 1. 19. 00:01
1. Overview Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable. The goal of multiple linear regression (MLR) is to model the linear relationship between the explanatory (independent) variables and response (dependent) variable. 2. Description 2.1 Formula 2.1.1..
-
Feature ScalingMLAI/Preprocessing 2020. 1. 18. 21:39
1. Issue Let's explain what its features scaling and why we need to do it. So as you can see we have these two columns age and salary that contain numerical numbers. Let's just focus on the age and the salary. You notice that the variables are not on the same scale because the age is going from 27 to 50. And the salaries going from 40K to like 90K. So because this age variable in the salary vari..
-
Categorical DataMLAI/Preprocessing 2020. 1. 18. 20:02
1. Overview 2. Description 2.1 Encode Categorical Data Since machine learning models are based on mathematical equations you can intuitively understand that it would cause some problem if we keep the text here and the categorical variables in the equations because we would only want numbers in the equations. So that's why we need to encode the catacombs variables. That is to encode the text that..
-
Missing DataMLAI/Preprocessing 2020. 1. 18. 18:36
1. Overview to start preparing the data so that our machine learning models run correctly and the first problem that we have to deal with is the case where you have some missing data in your data set and that happens quite a lot actually in real life. 2. Description 2.1 Handling Missing Data 2.1.1 Deletion to remove this line and remove this line but that can be quite dangerous because imagine t..
-
Insertion SortAlgoDS/Algorithm 2020. 1. 17. 19:13
1. Overview Insertion sort is a simple sorting algorithm that works the way we sort playing cards in our hands. It's one of the Greedy Algorithms. For nearly sorted data, consider that insertion sort is O(n) time. 2. Description 2.1 Procedure 12, 11, 13, 5, 6 Let us loop for i = 1 (second element of the array) to 4 (last element of the array) i = 1. Since 11 is smaller than 12, move 12 and inser..
-
Choosing sorting algorithmAlgoDS/Algorithm 2020. 1. 17. 19:12
1. Overview Compare each sorting algorithms 2. Description 2.1 Merge Sort Split your array in half. Recursively merge sort the left and right sub-arrays. Then, merge them together (linear time) to get the full sorted array. Pros: Has O(nlogn)O(nlogn) worst-case run time. Of the 3 algorithms here, it is the only one that is stable, so if you want to retain the ordering of comparatively equivalen..
-
Bubble sortAlgoDS/Algorithm 2020. 1. 17. 17:34
1. Overview Bubble Sort is the simplest sorting algorithm that works by repeatedly swapping the adjacent elements if they are in the wrong order. It's one of the Greedy Algorithms. 2. Description 2.1 Procedure Step 1: Starting with the first element(index = 0), compare the current element with the next element of the array. Step 2: If the current element is greater than the next element of the a..
-
StackAlgoDS/DataStructure 2020. 1. 16. 23:04
1. Overview Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). 2. Description 2.1 Operations 2.1.1 Push Adds an item in the stack. If the stack is full, then it is said to be an Overflow condition. 2.1.2 Pop Removes an item from the stack. The items are popped in the reversed..