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A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.
CEO pay includes salary, bonuses, stock sales, and other payments. Average CEO Pay is calculated using the last year a director sat on the board of each company. Stock returns do not include dividends. All directors refers to people who sat on the board of at least one Fortune 100 company between 2008 and 2012.
abess (Adaptive Best Subset Selection, also ABESS) is a machine learning method designed to address the problem of best subset selection.It aims to determine which features or variables are crucial for optimal model performance when provided with a dataset and a prediction task.
GitHub (/ ˈ ɡ ɪ t h ʌ b /) is a proprietary developer platform that allows developers to create, store, manage, and share their code. It uses Git to provide distributed version control and GitHub itself provides access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. [8]
There are 147 million housing units in the U.S., of which 86.6 million are owner-occupied and 34 million (or 40%) of which are mortgage-free.Of those carrying mortgage debt, almost all have fixed ...
A machine learning model is a type of mathematical model that, once "trained" on a given dataset, can be used to make predictions or classifications on new data. During training, a learning algorithm iteratively adjusts the model's internal parameters to minimize errors in its predictions. [ 85 ]