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Introduction to linear regression Linear regression application scenario House price forecast Sales quota forecast Loan line forecast What is linear regression Definition and formula Linear regression is an analytical method that uses regression equation (function) to model the relationship between one or more independent variables (eige ...

1 Introduction Similarity and dissimilarity are important concepts in machine learning, because they are adopted by many data mining technologies, such as common clustering, nearest neighbor classification and anomaly detection. In many cases, once we calculate the similarity or dissimilarity of eigenvectors, we no longer need the original dat ...

Once a day, never tired of learning Grid search The way to obtain an optimal super parameter can draw the verification curve, but the verification curve can only obtain one optimal super parameter at a time. If there are many permutations and combinations of multiple hyperparameters, grid search can be used to find the optimal hyperpara ...

reference material: https://gitee.com/datawhalechina/hands-on-data-analysis Chapter 3 model building and evaluation - Modeling After learning the knowledge points in the previous two chapters, I can process the data itself, such as adding, deleting, checking and supplementing the data itself, and do the necessary cleaning work. Then we'll sta ...

Automatic text classification technology liberates human beings from tedious manual classification, makes the classification task more efficient, and lays the foundation for further data mining and analysis. For news, short news introduction is a high summary of news content. The research on short text classification has always been a researc ...

1, K-fold cross validation If the given sample data is sufficient, a simple method for model selection is to randomly cut the data set into three parts, including training set, verification set and test set. The training set is used to train the model. Generally speaking, the amount of data is larger. The verification set is used to select the ...

1, VGG network VGG model is the second place in the 2014 ILSVRC competition, and the first place is GoogLeNet . But the VGG model works in multiple Transfer learning The performance in the task is better than Google net. VGG is a network developed from Alexnet. VGG has 19 layers (16 + 3) and five convolutions. Each convolution is followed by ...

Decision tree is a basic classification and regression method 1, Basic concepts of decision tree The nodes and directed edges of the decision tree are represented respectively: An internal node represents a feature or attributeLeaf nodes represent a classification.A directed edge represents a partition rule The directed edge of the decisio ...

machine learning Chapter 1: Fundamentals of machine learning Chapter 2: linear regression Chapter 3: logical regression Chapter 4: BP neural network Chapter 5: convolutional neural network Chapter 6: cyclic neural network Chapter 7: decision tree and random forest Chapter 8: support vector machine Chapter 9: Hidden Markov Chapter 10: clusteri ...

1, Introduction 1 threshold The simplest way to block an image is to set a threshold to binarize the image. How should we choose this threshold For the image with obvious boundary in the histogram of the image, we can easily find this threshold, but if the boundary of the histogram of the image is not obvious, it will become very difficult to ...