Super parameter adjustment and automatic time series modeling are carried out by genetic algorithm
In previous articles, we introduced some knowledge based on genetic algorithm. This article will use genetic algorithm to process machine learning model and time series data.Super parameter adjustment (TPOT)Automatic machine learning (Auto ML) helps us find the most suitable model for prediction by automating the whole machine learning process. ...
Added by VMinder on Fri, 31 Dec 2021 16:05:22 +0200
Question 3 of "Teddy Cup" C of data mining in 2018
1, Problem background
Topic: analysis of tourists' destination impression
Improving the reputation of scenic spots, hotels and other tourism destinations is a work that local cultural and tourism authorities and tourism related enterprises attach great importance to and pay attention to. It involves important matters such as how to stabilize ...
Added by davieboy on Thu, 30 Dec 2021 17:30:29 +0200
Research on traffic casualty accident prediction based on extended tecdat|R language Markov transformation model
Original link: http://tecdat.cn/?p=12227Original source: Tuo end data tribal official accountabstractThis paper describes the analysis process of Markov transformation model in R language. Firstly, the simulation data set is modeled in detail. Next, the Markov transformation model is fitted to a real data set with discrete response variables. D ...
Added by Shit4Brains on Mon, 27 Dec 2021 04:57:52 +0200
IO flow overview and classification [understanding]
IO stream introduction
IO: input / output Stream: an abstract concept, which is the general term for data transmission In other words, the transmission of data between devices is called stream, and the essence of stream is data transmission IO stream is used to deal with data transmission between devices Common applications: file replica ...
Added by godwheel on Sun, 26 Dec 2021 21:34:13 +0200
Twenty lines of Python code crawl microblog high-quality beauty video (Welfare)
Brothers, if you don't send high-quality reptiles, you won't see it. Alas~So you are all such people!!!You've been paying attention to me for so long. Of course, you should have some serious teaching videos. After all, it's not serious. Everyone doesn't watch it. I'll climb a little sister for you today.The environment used is Python 3 6 and py ...
Added by php-phan on Sun, 26 Dec 2021 09:48:09 +0200
Supervised algorithm KNN
Supervised algorithm KNN/K nearest neighbor
1: Principle
1. Calculate the Euclidean distance from o point to all points
Oh
Surname
distance
leave
:
d
...
Added by andrewholway on Sun, 26 Dec 2021 07:13:43 +0200
R language nonlinear regression nls exploration and analysis of river stage flow data, rating curve and flow prediction visualization
Original link: http://tecdat.cn/?p=24761 This document uses some exploratory data analysis to develop the rating curve and flow prediction of the river. The purpose is to create and update rating curves using (1) instantaneous flow measured during periodic deployment of bottom mounted units and (2) instantaneous depth measurements from water le ...
Added by dlebowski on Fri, 24 Dec 2021 10:53:49 +0200
Practical case | Python credit card fraud detection based on machine learning!
Welcome to focus on Python, data analysis, data mining and fun tools!
When we buy products online, many people like to use credit cards. But credit card fraud often happens around us. Network security is becoming a vital part of our life.
In order to solve this problem, we need to use machine learning algorithm to build an abnormal behavior ...
Added by lmhart on Thu, 23 Dec 2021 01:30:37 +0200
Introduction to data analysis task4
This record is my learning notes for participating in datawhale data analysis (Titanic mission project). Please give me more advice on the shortcomings. Data visualization Mainly introduce Python data visualization libraries Matplotlib and seaborn. You may find the data very interesting in the study of this chapter. In the process of playing th ...
Added by curtis_b on Tue, 21 Dec 2021 22:20:33 +0200
[data analysis and visualization] key points of data drawing 6 - too many data groups
Data drawing point 6 - too many data groups
Comparing the distribution of several numerical variables is a common task in data presentation. The distribution of variables can be represented by histogram or density diagram. It is very attractive to represent groups of appropriate data on the same axis. However, too many data groups will serious ...
Added by matthewst on Mon, 20 Dec 2021 10:07:41 +0200