random

问题 I want to draw a random sample from my dataset, using different proportions for each value of a factor variable, as well as using weights stored in some other column. dplyr solution in pipes will be preferred as it can be inserted easily in long code. Let's take the example of iris dataset. Species column is divided into three values 50 rows each. Let's also assume the sample weights are stored in column Sepal.Length . If I have to sample equal proportions (or equal rows) per species, the

问题 I want to draw a random sample from my dataset, using different proportions for each value of a factor variable, as well as using weights stored in some other column. dplyr solution in pipes will be preferred as it can be inserted easily in long code. Let's take the example of iris dataset. Species column is divided into three values 50 rows each. Let's also assume the sample weights are stored in column Sepal.Length . If I have to sample equal proportions (or equal rows) per species, the

问题 I need to write a program that generates N random numbers and write them to binary file in descending order. It should be done without using any of sorting algorithms that use main memory. This is what I've done so far: #include <iostream> #include <fstream> #include <ctime> #include <cstdlib> using namespace std; int main () { srand(time(0)); rand(); int N; do{ cout << "Unesite N: "; cin >> N; } while(N<=0); ofstream br("broj.dat", ios::binary | ios::trunc); for(int i = 0; i<N; i++){ int a =

问题 I've used random.normal() in the past to generate a single number who, if called multiple times, in aggregate would create a bell curve distribution. What I'm trying to do now is to create the opposite / inverse, where the distribution is biased towards the extremes within a range? There are built in functions in excel that seem to do what I want. Is there a way to do it in python? Thank you 回答1: It appears you want a distribution with an "upside-down bell curve" compared to the normal

问题 I've used random.normal() in the past to generate a single number who, if called multiple times, in aggregate would create a bell curve distribution. What I'm trying to do now is to create the opposite / inverse, where the distribution is biased towards the extremes within a range? There are built in functions in excel that seem to do what I want. Is there a way to do it in python? Thank you 回答1: It appears you want a distribution with an "upside-down bell curve" compared to the normal

问题 I have a problem that seems small, but it is no longer making me sleep at night, I am probably thinking about it too much and I have lost sight of the correct path! I'm using Bootstrap 4 as Framework. I have to insert an automatic, interaction-free, full-page Carousel that displays images in random order each time the page is refreshed. It has to get the images from a specific folder, because I have a large number of images. Anyone can help me with the Javascript that i need for do that??

问题 I'm trying to make a word game. First of all, the index will be white. if user Click the correct answer then index will be to green color and go to next screen, also index will be white in next screen.. again if user click incorrect answer then index will be to red color and don't let go to the next page until user put correct answer... i set a GridView in Swiper (Swiper took by importing, import 'package:flutter_swiper/flutter_swiper.dart';). and i want to show next index of Swiper after

问题 I'm trying to make a word game. First of all, the index will be white. if user Click the correct answer then index will be to green color and go to next screen, also index will be white in next screen.. again if user click incorrect answer then index will be to red color and don't let go to the next page until user put correct answer... i set a GridView in Swiper (Swiper took by importing, import 'package:flutter_swiper/flutter_swiper.dart';). and i want to show next index of Swiper after

问题 I need to generate a vector sampled uniformly with 10 directions (a collection of 10 random numbers) which lies over a unit sphere. So, the sum of the squares of the 10 values should be 1. This is the exact question for which I need to generate those points: Implement the Perceptron algorithm and run it on the following synthetic data sets in ℝ 10 : pick 𝑤∗ = [1,0,0,…,0]; generate 1000 points 𝑥 by sampling uniformly at random over the unit sphere and then removing those that have margin 𝛾

问题 I need to generate a vector sampled uniformly with 10 directions (a collection of 10 random numbers) which lies over a unit sphere. So, the sum of the squares of the 10 values should be 1. This is the exact question for which I need to generate those points: Implement the Perceptron algorithm and run it on the following synthetic data sets in ℝ 10 : pick 𝑤∗ = [1,0,0,…,0]; generate 1000 points 𝑥 by sampling uniformly at random over the unit sphere and then removing those that have margin 𝛾