Tag: prediction

Game player behavior data analysis and prediction based on python

Analysis and prediction of game player behavior data 1. Introduce project background and analysis objectives 1. Requirements and application scenarios With the continuous development of the game industry, more and more game companies need to conduct data analysis on game operations to optimize operation strategies and improve user retention and revenue. Analysis of game operations […]

Python data analysis case 28 – traffic accident prediction in Seattle (unbalanced sample processing)

This case is suitable for students in the direction of machine learning data science. Introduction (nonsense collection) Traffic accidents are a serious public safety problem, and thousands of people die in traffic accidents every year around the world. With the development of transportation and the acceleration of urbanization, traffic accidents have become one of the […]

Feature scaling (Scale Features), feature scaling prediction? CO2 value, df column index expansion

Directory 1. Feature scaling 2. Predict CO2 value 3, df column index expansion 1. Feature scaling Feature scaling can be used for different units of measure. In the case of different measurement units, the numerical size of the features will also be different, which may affect the performance of some machine learning algorithms. For example, […]

Mathematical Modeling – Gray Prediction Model with Matlab Code

Directory 1. Interpretation of Gray Prediction 2. Examples of gray prediction 3. Gray prediction model 3.1 Generate cumulative data 3.2 Accumulated data expression 3.3 Solve unknown parameters 4. Partial code of gray prediction Matlab 5. Forecast results 1. Gray forecast interpretation Gray prediction is a method to predict the system with uncertain factors. Gray prediction […]

Prediction of time-consuming cargo transportation based on XGBOOST model – Part 3 XGBOOST and LightGBM optimal selection model

When the amount of data is large, LightGBM will be significantly faster than XGBOOST, but the prediction accuracy of XGBOOST will be higher. from sklearn.preprocessing import OneHotEncoder from xgboost import XGBRegressor # read historical data history_data = df_replen_2[[‘mot’, ‘country’, ‘priority’, ‘cc’, ‘climate_count’,’shippingfrequency’,’isgreen’, ‘holiday_count’,’forwarder’, ‘dayofweek’,’ts_pu_hour’, ‘ lt_pu_pod’]] # Select the feature columns to use feature_cols = […]

Prediction of time-consuming cargo transportation based on XGBOOST model – Part 1 Acquisition of weather warning data

Construct models based on data obtained from the Internet Background: 1. The transportation time will be affected by bad weather factors, such as heavy fog/thunderstorm/typhoon, etc. Regardless of whether it is air or sea transportation, bad weather may be encountered before and during takeoff, which may cause delays in takeoff, which will also affect our […]

Python case analysis: Classification prediction using LightGBM algorithm, random forest, and five-fold cross-validation

1. Data import import pandas as pd import numpy as np import warnings from imblearn import under_sampling, over_sampling from imblearn.over_sampling import SMOTE warnings. filter warnings(‘ignore’) pd.options.display.max_columns = None #Display all columns pd.set_option(‘display.float_format’, lambda x: ‘%.2f’ % x) #Cancel scientific notation train_data = pd.read_csv(‘Training.csv’) test_data = pd.read_csv(‘Test.csv’) 2. Data cleaning #Merge data total_data = pd. concat([train_data, […]

Interval prediction | MATLAB implements QGPR Gaussian process quantile regression time series interval prediction

Interval prediction | MATLAB implements QGPR Gaussian process quantile regression time series interval prediction Table of Contents Interval prediction | MATLAB implements QGPR Gaussian process quantile regression time series interval prediction List of effects basic introduction Model description programming References List of effects Basic introduction MATLAB implements QGPR Gaussian process quantile regression time series interval […]

[Computer Vision] CLIP combat: Zero-Shot Prediction (including source code)

1. Code combat The code below performs zero-shot prediction using CLIP. This example takes an image from the CIFAR-100 dataset and predicts the most likely label out of the 100 text labels in the dataset. import os import clip import torch from torchvision.datasets import CIFAR100 # Load the model device = “cuda” if torch.cuda.is_available() else […]