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summary: 1. When calculating the effect coefficient of outlier interval in the sequence, such as holiday coefficient, the increased non outlier interval on the left and right sides should be as long as possible. The stronger the degree of outlier, the longer the increased non outlier interval, Polynomial and Lowess can not be pulled up. Since ...

Original link: http://tecdat.cn/?p=18359 Original source: Tuo end data tribal official accountPower load forecasting is the basis of power grid planning, and its level will directly affect the quality of power grid planning. In order to accurately predict power load, it is necessary to model. In this paper, quantile regression, GAM spline curve ...

Measuring the performance of clustering algorithm is not simply counting the number of errors or calculating the precision and recall in supervised classification algorithm. There are many evaluation indicators for clustering algorithms. This paper is mainly based on the sklearn machine learning library, which provides a series of measu ...

This paper mainly starts with the mathematical principle, and discusses how to make the computer learn the linear regression equation through the known data. Before we go into detail, let's take a look at an example. This is a statistical table about the amount of bank loans. It can be seen that in this example, the bank loan amount is relat ...

Chapter 5 logistic regression algorithm    based on the linear regression algorithm, the logical regression algorithm constructs the conversion function of the dependent variable y, and divides the number of Y into two or more categories of 0-1, so as to realize the classification fitting and prediction of things. 5.1 from linear re ...

1, Basic knowledge of cluster analysis Cluster analysis is also called clustering. It is different from classification. The target variables of classification are known. Each sample has a class label, and the target variables of clustering are unknown in advance. The sample categories of clustering are not defined in advance. Clustering is div ...

Official account: Special HouseAuthor: PeterEditor: Peter Hello, I'm Peter~ Scikit learn is a well-known Python machine learning library, which is widely used in data science fields such as statistical analysis and machine learning modeling. Modeling invincible: users can realize various supervised and unsupervised learning models through ...

catalogue 1 integrated learning 2 random forest classifier 2.1 random forest classifier function and its parameters 2.2 construction of random forest 2.3 comparison of random forest and decision tree under cross validation 2.4 drawing n_ Learning curve of estimators 3 random forest regressor 3.1 random forest classifier function and its ...

In this paper, we will use the deep learning method (LSTM) to perform multivariate time series prediction.Let's start with two topics——What is time series analysis?What is LSTM?Time series analysis: time series represent a series of data based on time sequence. It can be seconds, minutes, hours, days, weeks, months and years. Future ...

Main sources: Mr. Li Mu's pytorch hands-on learning and deep learning (bow and thank you) Record what you have learned every day. Welcome to discuss~ (the dust has finally settled in the senior year, and I am fully engaged in learning during the holiday!) 1. What is regularization? Regularization can be translated as regularization or nor ...