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This article is excerpted from Blob Detection Using OpenCV ( Python, C++ ) The summary of image block detection methods is used for later learning and engineering application.   § 00 preamble This article is excerpted from Blob Detection Using OpenCV ( Python, C++ ) The summary of image block detection methods is u ...

Original link: https://blog.csdn.net/weixin_40571937/article/details/103518331 Reference source: https://blog.csdn.net/mr_corder/article/details/82492981 I The concept of reinforcement learning (reinforcement learning): Machine learning algorithms can be roughly divided into the following three types: Supervised learning (e.g. regression, cl ...

1. Feature digitization 1.1 Replace() function import pandas as pd df = pd.DataFrame({"gene_segA": [1, 0, 0, 1, 1, 1, 0, 0, 1, 0], "gene_segB": [1, 0, 1, 0, 1, 1, 0, 0, 1, 0], "hypertension": ["Y", 'N', 'N', 'N', 'N', 'N', 'Y', 'N', 'Y', 'N'], "Gallstones": ['Y', 'N', 'N', 'N', 'Y', 'Y', 'Y', 'N', 'N', 'Y'] }) df df.replace({"N": 0, 'Y': ...

Feature category Common feature types include: numerical feature, category feature, sequence feature, k-v feature, embedding feature, cross feature, etc. 1. Numerical characteristics Numerical features are the most common, such as some statistical features: ctr, click_num, etc. in different business scenarios, the amount of numerical feature ...

Detailed tutorials can be used for reference Official documents 1, Installation instructions Before installing PaddleDetection, you need to install dependency PaddlePaddle first. You can think of it as a kernel and install PaddleDetection with it. First, we can create a new virtual environment named paddle and activate the environment. cond ...

Background knowledge required for reading this article: hard interval support vector machine, relaxation variables, yidui programming knowledge1, Introduction   in the previous section, we introduced a most basic support vector machine model - hard interval support vector machine. This model can classify linearly separable data sets, ...

Data preprocessing process thinking import pandas as pd import numpy as np data fetch train = pd.read_csv("preprocess/train.csv") test = pd.read_csv("preprocess/test.csv") Stochastic forest model prediction Feature selection – Pearson correlation coefficient (train.shape, test.shape) ((201917, 1700), (123623, 1699)) # Ext ...

Ox tail sweeps the shadow and tiger head opens the blind box. Three volume online disc competition, ranking evaluation 0.59168 Baidu online AI competition: document image shadow elimination, and the prize pool is a mysterious gift package. The prize pool is a blind box. I'm a little curious. 1, Document image shadow elimination In life, whe ...

Baidu cloud link of the file used in this article: Link: https://pan.baidu.com/s/15-qbrbtRs4frup24Y1i5og Extraction code: pm2c linear prediction Assuming that a set of data conforms to a linear law, we can predict the data that will appear in the future a b c d e f g h .... ax + by + cz = d bx + cy + dz = e cx + dy + ez = f In ...

Implementation of keras version of DeepLab-V3 + semantic segmentation Neural Network network structure Deeplab series network models are developed from ResNet residual module, and on this basis, they are integrated with the implementation of empty convolution. Compared with Deeplab v3, Deeplab v3 + introduces the encoder decoder structure c ...