Programming VIP

1. Main content of the article This blog is devoted to explaining the skills to encapsulate code in PyCharm and invoke it in JupyterNoteBook. Through the learning of this blog, taking KNN algorithm as an example, it is intended to grasp the skills of functional code in plain language. It takes about 5 minutes to read this blog. Note: the c ...

Friendly participation: @Cotton cotton YOLO is a target detection method, which is characterized by fast detection and high accuracy. The author regards the target detection task as a regression problem of target region prediction and category prediction. This method uses a single neural network to directly predict the boundary and cate ...

In this article, first briefly explain what the mixed density network (MDN) is, then build the MDN model using Python code, and finally use the built model for multiple regression and test the effect.regression"Regression prediction modeling is to approximate the mapping function (f) from input variable (X) to continuous output variable (y ...

Algorithm Introduction k-nearest neighbor method belongs to supervised learning and does not need training model (lazy learning). Algorithm flow: for the test samples, find k training samples from the given training set according to some distance measurement (Minkowski distance, Euclidean distance, Manhattan distance, Chebyshev distance, e ...

Datawhale zero foundation entry data mining Task5 model fusion 5, Model fusion Game Title: Zero basic entry data mining - used car transaction price prediction 5.1 model fusion objectives Model fusion is carried out for the models completed by multiple parameters adjustment.Complete the fusion of multiple models. 5.2 content introduction ...

Premise: import pandas as pd import numpy as np import os import seaborn as sns from pyod.models.mad import MAD from pyod.models.knn import KNN from pyod.models.lof import LOF import matplotlib.pyplot as plt from sklearn.ensemble import IsolationForest 1.IQR python deletes outliers based on IQR: df = pd.read_excel('./7.xlsx') def fit_mod ...

Classification of film reviews using naive Bayes 1. Data set explanation: The data set is a subset of IMDB movie data set, which has been divided into test set and training set. The training set includes 25000 movie reviews, and there are 25000 test sets. The data set has been preprocessed to convert the specific word sequence of each rev ...

This practical project is based on the dataset of Lending Club [dataset address: https://github.com/H-Freax/lendingclub_analyse/data/ ] This practical project is based on Colab environment brief introduction This practical project of data analysis is divided into two parts. The first part mainly introduces the Baseline method based on Lig ...

Image features Similar to text features, image features are also a kind of data that is very difficult to mine by gradient lifting tree model. At present, image related problems, such as image classification and image segmentation, are almost neural network-based models. However, in some multimodal problems, such as commodity search recommen ...

Machine learning algorithms usually use cross validation techniques such as kFold to improve the accuracy of the model. In the process of cross validation, the prediction is carried out through the split test set that is not used for model training. These predictions are called out of fold predictions. External prediction plays an important rol ...