Tag：Model

QT quick 3D – dynamically load 3D models
QT quick 3D – dynamically load 3D models

Mathematical modeling algorithm: grey prediction model GM (1,1) and Python code
Grey prediction model GM (1,1) Grey prediction model\(GM(1,1)\)It is a commonly used prediction method in mathematical modeling competitions, and it is often used for medium and shortterm prediction that conforms to the exponential law. Its mathematical expression and principle analysis refer to the web page and literature at the end of the article. Pretreatment The […]

Python technique 32: skills when functions are used as parameters
We were inPython technique 3: anonymous functions, callback functions, highorder functionsAs mentioned in, you canlambdaExpression to set the default parameters for the function, so as to modify the number of parameters of the function: import math def distance(p1, p2): x1, y1 = p1 x2, y2 = p2 return math.hypot(x2 – x1, y2 – y1) points […]

R language uses comprehensive information criteria to compare stochastic volatility (SV) models to model stock price time series
Original link: http://tecdat.cn/?p=23882 abstract Stochastic volatility (SV) model is a series of models commonly used in stock price modeling. In all SV models, volatility is regarded as a random time series. However, there are still great differences between SV models from the perspective of basic principles and parameter layout. Therefore, selecting the most appropriate SV […]

Review of word alignment task 2022
What is word alignment Word alignment in machine translation. It can be regarded as a sub derivative of machine translation. Word alignment is the task of finding the responsibility between source and target words in a pair of senses that are translations of each otherGenerally, this correspondence will be expressed as a correlation matrix like […]

R language finite mixed model clustering FMM, generalized linear regression model GLM mixed application analysis whisky market and research patent applications, expenditure data
Original link:http://tecdat.cn/?p=24742 abstract Finite mixture model is a popular method to model or approximate general distribution function of unobserved heterogeneity. They are used in many different fields, such as astronomy, biology, medicine or marketing. This paper gives an overview of these models and many application examples. introduce Finite mixture model is a popular method to […]

Scatter fitting circle —ransac
1、 Algorithm principle Random sample consistency(Random Sample Consensus RANSAC）It is an iterative method used to estimate a mathematical model from observed data containing outliersparameterTherefore, it can also be understood as aOutlier detectionmethod. One of RANSACBasic assumptionsYes, the data isinterior point(“inliers”) andOuter point(“outliers”), whereinterior pointIt is data that can be explained by some model parameters within […]

Hot spots in August: easydl image segmentation data is automatically labeled, and the labeling efficiency is improved by 30 times+
This month, easydl’s tiny target detection function was launched, and the target pixel is less than 5% of the full image, which can also be accurately captured! The maximum effect is increased by 45%; Easydl image segmentation starts the automatic fitting and labeling mode, and the automatic labeling is completed by automatically identifying the target […]

Python uses pystan Bayesian IRT model to fit Rasch model to analyze student examination question data
Original link: http://tecdat.cn/?p=26769 Because there are too many students and insufficient teaching assistants in a university, it is necessary to impose a five question limit on the number of questions given to each student in the midterm examination. All questions that must be used must come from a test library of about 400 pre approved […]

Extended tecdatr language keras uses RNN, bidirectional RNNs recurrent neural network, LSTM analysis and prediction of temperature time series, IMDB film scoring emotion
Original link:http://tecdat.cn/?p=23616 In this article, we will review three advanced methods to improve the performance and generalization ability of recurrent neural networks. We will demonstrate these three concepts on a temperature prediction problem. We use time series of data points from sensors installed on the roof of buildings. summary The time series of data points […]

Multimix: a small amount of supervision from medical images, interpretable multi task learning
In this article, I will discuss a new semi supervised, multi task medical imaging method called multimix, Ayana Haque (me), Abdullah al zubaer Imran, Adam Wang, Demetri terzopoulos. The paper was included by isbi 2021 and published at the conference in April. Multimix performs joint semi supervised classification and segmentation by using a confidence based […]

Interpretable AI (Xai): how to better explain the prediction of the model using life and shake
As data scientists or machine learning practitioners, integrating interpretability into machine learning models can help decision makers and other stakeholders have more visibility and understand the interpretation of model output decisions. In this article, I will introduce two models, life and shake, which can help understand the decisionmaking process of the model. Model We will […]