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| def text_wrap(text, font, max_width): | |
| """Wrap text base on specified width. | |
| This is to enable text of width more than the image width to be display | |
| nicely. | |
| @params: | |
| text: str | |
| text to wrap | |
| font: obj | |
| font of the text |
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| #include<iostream> | |
| void swap(int& a, int& b){ | |
| // Swap 2 numbers using a temporary variable. | |
| int temp; | |
| temp = a; | |
| a = b; | |
| b = temp; | |
| } | |
| int* sort(int a[]){ |
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| pragma solidity ^0.4.24; | |
| import {count} from './libraryF.sol'; | |
| contract Math{ | |
| using count for count.hold; | |
| using count for uint; | |
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| pragma solidity ^0.4.24; | |
| library count{ | |
| struct hold{ | |
| uint a; | |
| } | |
| function subUint(hold storage s, uint b) public returns(uint){ | |
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| 0x6fC70d74Da267f7b551809993A45c9CF487955e5 |
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| let articleData={ | |
| 'logo':'public/images/medium.png', | |
| article :[ | |
| { | |
| id: 1, | |
| author: 'eyong kevin', | |
| title: 'Linear Regression: How to overcome underfitting with locally Weight Linear Regression(LWLR)', | |
| description: 'Here, we will look at a technique for locally smoothing our estimates to better fit data', | |
| url: 'https://itnext.io/linear-regression-how-to-overcome-underfitting-with-locally-weight-linear-regression-lwlr-e867f0cde4a4', | |
| clapps: 39, |
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| import React, { Component } from 'react'; | |
| export default class Article extends Component { | |
| render() { | |
| return ( | |
| <div className='item'> | |
| <div className='image'> | |
| <img src='public/images/articles/LWLR.jpg' /> | |
| </div> | |
| <div className='middle aligned content'> |
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| def lwlr(testPoint, xArr, yArr, k=0.1): | |
| """ | |
| Generate an estimate for any point in the x space | |
| Parameters | |
| ---------- | |
| testPoint: float | |
| point in the x space | |
| xArr : List | |
| Our data |
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| def standRegres(xArr, yArr): | |
| """ | |
| Find weight given the data and the predicted value | |
| Parameters | |
| ---------- | |
| xArr : List | |
| Our data | |
| yArr: List |
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| # Load data | |
| def loadDataSet(filename): | |
| """ | |
| load dataset into data-matrix and label-matrix | |
| Parameters | |
| ---------- | |
| filename : String | |
| File path containing the data | |
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