Explanatory Analysis of the XGBoost Model for Budget Deficits of U.S.

The debt ceiling was always an issue in the United States. As of today, the national government debt has reached the debt ceiling, which is $31.4 trillion. The authorities have warned of chaotic consequences if Congress no longer approves the debt ceiling. The U.S. government has managed an annual deficit of approximately $1 billion sinceContinue reading “Explanatory Analysis of the XGBoost Model for Budget Deficits of U.S.”

Asia Against Dollar: Forecasting with Modeltime

While the US midterm election escalated, the dollar’s performance weakened; especially this situation happened against the Asian currencies. South Korean won(KRW) is the best performer among them. The Chinese yuan(CNY) was behind its counterparts because of their aggressive public health measures related to the zero-COVID protocol. Let’s add the Japanese yen(JPY) and Malaysian ringgit(MYR) toContinue reading “Asia Against Dollar: Forecasting with Modeltime”

The Effect of Early Childhood Education on Wealth: Modeling with Bayesian Additive Regression Trees (BART)

Recently, I read a tweet that reports children who grow up in poor conditions earn much less as adults than those with better conditions. I believe one of the best ways to check that is to compare childhood education participation rates with wealth in related countries; to do that, I will use early childhood educationContinue reading “The Effect of Early Childhood Education on Wealth: Modeling with Bayesian Additive Regression Trees (BART)”

Modeling the Extinction of Species with SVM-Kernel

In the last article, we analyzed carbon emissions and the effects that created them. This time I want to look into another important environmental issue, animal biodiversity; by animals, I mean mammals, birds, fish, reptiles, and amphibians. The metric we are going to be interested in is the living planet index which measures the changeContinue reading “Modeling the Extinction of Species with SVM-Kernel”

Food Crisis Analysis and, Forecasting with Neural Network Autoregression

The war between Russia and Ukraine has affected the global food supply other than many vital things. Primarily cereal crop products have been affected the most because the imports have been provided to the world mainly through Ukraine and Russia. Let’s check the situation we’ve mentioned for G20 countries. We will get a look atContinue reading “Food Crisis Analysis and, Forecasting with Neural Network Autoregression”

Nuclear Threat Projection with Neural Network Time Series Forecasting

Unfortunately, we have been through tough times recently as going on Russian invasion in Ukraine. As Putin stacked to the corner via sanctions and lost in the field, he has been getting to be more dangerous. He has even threatened to use nuclear weapons if necessary. Because of the nuclear danger we’ve just mentioned above,Continue reading “Nuclear Threat Projection with Neural Network Time Series Forecasting”

Meta-Learning: Boosting and Bagging for Time Series Forecasting

I am always struggled to model the changes in gasoline prices as a categorical variable, especially in a small amount of time-series data. The answer to improving the performance of modeling such a dataset can be to combine more than one model. This method of combining and aggregating the predictions of multiple models is calledContinue reading “Meta-Learning: Boosting and Bagging for Time Series Forecasting”

Plotly for Data Visualization: The Vaccinations Effect on Covid-19

One of the most frequently asked questions these days is whether the vaccine works in reducing the number of cases and deaths. In order to examine that we will build a function so that we can run for every country we want without repeating the same code block. The dataset we’re going to use forContinue reading “Plotly for Data Visualization: The Vaccinations Effect on Covid-19”

Comparing the Coronavirus Pandemic (COVID-19) Management for some Developed Countries

The pandemic continues at full speed in Turkey where I live, because the government doesn’t conduct the process well; the data they provide is so doubtful, and the decisions they made are very inconsistent. So, I wondered about the situation in the other part of the world, especially the developed countries. In order to that,Continue reading “Comparing the Coronavirus Pandemic (COVID-19) Management for some Developed Countries”