• ## Classification of machine learning: prediction bias

Time：2021-9-29

The logistic regression prediction should be unbiased. That is, the “predicted average” should be approximately equal to the “observed average”Prediction deviationIt refers to the difference between the two averages. Namely:Forecast deviation = forecast average – the average of the corresponding labels in the datasetNote: “forecast deviation” is not the same as “Deviation” (“B” in “Wx […]

• ## Extension data tecdat: how to build an integration model in machine learning with R language?

Time：2021-8-9

Original link:http://tecdat.cn/?p=6608 Original source:Tuo end data tribal official account introduce In this article, I will introduce you to the basics of integrated modeling. In addition, in order to provide you with practical experience in integration modeling, we will use r for integration. 1. What is integration? Generally, integration is a technology that combines two or […]

• ## C + + homework – score statistics

Time：2021-6-28

Achievement statistics 1) Write a function randscore to generate an integer of [0100] interval（ Tip: use rand function) int randScore(){ int num = rand() % 101; return num; } 2) Write a function, using the above randscore function, randomly generate the results of a course for the whole class. void stuRandomScore(int stuScore[]){ for (int i […]

• ## Can app startup really reduce startup time

Time：2021-6-2

preface Previously, we talked about some common ways to start optimization, but some of our little friends disdain it “These methods have been known for a long time. Don’t you know how to say something new? Like app startup? Can it help start optimization? “ OK, since you have asked sincerely, I will tell you […]

• ## Python and R use exponential weighted average (EWMA), Arima autoregressive moving average model to predict time series

Time：2021-5-6

Link to the original text:http://tecdat.cn/?p=21773 summary Learn the steps to create a time series forecast Focus on Dickey fuller test and ARIMA model Learn these concepts in theory and their implementation in Python introduce Time series (from now on called TS) is considered to be one of the little-known skills in the field of data […]

• ## Introduction to pandas (1)

Time：2021-4-14

Data analysis and processing library import pandas as pd df=pd.read_csv(“./pandas/data/titanic.csv”) df.head (N) Read the first n rows of data df.head(6) df.info () get a brief summary of the dataframe df.info() <class ‘pandas.core.frame.DataFrame’> RangeIndex: 891 entries, 0 to 890 Data columns (total 12 columns): # Column Non-Null Count Dtype — —— ————– —– 0 PassengerId 891 […]

• ## Introduction to pandas (3)

Time：2021-4-6

Time format and time query import pandas as pd date=pd.Timestamp(‘2020/09/27 13:30:00’) print(date) 2020-09-27 13:30:00 #Year print(date.year) #Month print(date.month) #Day print(date.day) #Time print(date.hour) #Points print(date.minute) #Seconds print(date.second) 2020 9 27 13 30 0 #Plus 5 days date+pd.Timedelta(‘5 days’) Timestamp(‘2020-10-02 13:30:00’) #Time conversion res=pd.to_datetime(‘2020-09-10 13:20:00’) print(res.year) 2020 #Generate a column of data se=pd.Series([‘2020-11-24 00:00:00′,’2020-11-25 00:00:00′,’2020-11-26 00:00:00’]) print(se) […]

• ## Wall crack recommended! This network investigation tool, can be called artifact!

Time：2021-1-21

MTR is a very useful network analysis tool. I believe many people have used it, because it is often used in personal work to analyze the network situation, and it is very simple and practical. Today, brother migrant workers will introduce and recommend it to you. 1. Introduction to MTR MTR is a very good […]

• ## Hypothesis test: use the p value to accept or reject your hypothesis

Time：2020-10-23

AuthorCompile | VKSource | analytics vidhya introduce Test is one of the most basic concepts in statistics. Not only in data science, hypothesis testing is very important in various fields. Want to know how to do it? Let’s take an example. Now there’s a lifebuoy shower gel. Shower Gel manufacturers claim it kills 99.9% of […]

• ## How to accurately evaluate the fluency of Android applications?

Time：2020-8-18

Brief introduction of the author: Ye FangzhengHe joined Tencent in 2008 and worked in the special test group of wireless R & D department. He has been responsible for the performance optimization of several products and accumulated a lot of experience in mobile terminal platform optimization and evaluation. How to get SM value? By measuring […]

• ## [RL] prediction and control mc, TD (λ), SARS a, Q-learning, etc

Time：2020-8-1

This intensive learning series is based on the learning link to David Silverhttp://www0.cs.ucl.ac.uk/staff/D.Silver/web/Teaching.html After introducing the basic concepts of RL and MDP in the previous article, this paper introduces the basic concepts of RL and MDPmodel-freeIn this case (i.e. do not know the return RS and the state transition matrix PSS’), how to proceedpredictionThat is […]

• ## Forecasting house price: the return problem of artificial intelligence

Time：2020-7-1

We have raised three classic questions Dichotomous problem (judgment of the tendency of good and bad film reviews) Multi classification problem (classifying news by topic) Regression problem (estimating real estate prices based on real estate data) We have solved the first two problems, and today we have solved the third problem, the problem of return. […]