K-medoids is another clustering algorithm that can be used to find groups in a dataset. K-medoids clustering is very similar to k-means clustering, except for...
The training process of neural network is a challenging optimization process and usually cannot converge. This may mean that the model at the end of...
Abstract: What is data mining? What is machine learning? What about Python data preprocessing? This paper will lead everyone to understand data mining and machine...
99% expected gap [...] With 99. At 99% confidence level [...] Expected gap on [...] Corresponds to approximately 99.6% to 99. For any (absolutely) continuous...
The first time they contacted IP Geolocation, they spent two days to roughly understand what problems they had solved in their previous work, and the...
This paper considers classification prediction based on kernel method. Note that we are not using standard logistic regression here; it is a parametric model. There...
In regression modeling studies, we will discuss optimization, and the classical tool is called conjugation. The visualization considers a simple parabolic function (in dimension 1)...
Deep learning is everywhere. In this article, we will use Keras for text categorization. For demonstration purposes, we will use 20 newsgroup data sets. The...
The home appliance industry and consumers are quietly upgrading. Such changes in the market make consumers' expectations of home appliances no longer a simple function...
As software packages advance, it becomes easier to use generalized linear mixed model (GLMM) and linear mixed model (LMM). As we find ourselves using these...
Here, we use TensorFlow to realize a neural network with three layers, namely input layer, hidden layer and output layer. from tensorflow.examples.tutorials.mnist import input_data mnist...
In this article, we will introduce regression modeling in a Bayesian framework and use the PyMC3 MCMC library for reasoning. We will first review the...
This article is about extreme value inference. We use the maximum likelihood method on the generalized Pareto distribution. In the context of parametric models, the...
We discuss methods of using programs to obtain confidence intervals for predictions. We're going to talk about linear regression. > points(x,predict(reg,newdata= data. We're making a...
In this paper, 188 countries are aggregated based on these 19 socioeconomic indicators using monte-Carlo K-means clustering algorithm implemented by Python. Clustering can help reduce...
Today's topic is therapeutic effects in Stata. The treatment effect estimator estimates causality of treatment to outcome based on observational data. As with any regression...
In this example, the neural network was used to predict the power consumption of citizens' offices using data from April 2011 to February 2013. Daily...
In this article, we will see how to create a language translation model, which is a well-known application of neural machine translation. We will use...