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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 ...
One of the first completely free to use and open source statistical software was R, first released in 2000. [1] Some of the free software packages are from governments, for example Epi Info, which is from CDC [4] (Centers for Disease Control and Prevention). Some other software packages are from smaller or independent organizations or universities.
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]
Academic Torrents [1] [2] [3] [4] [5] [6] is a website which enables the sharing of research data using the BitTorrent protocol. The site was founded in November 2013 ...
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
gretl is an example of an open-source statistical package. ADaMSoft – a generalized statistical software with data mining algorithms and methods for data management; ADMB – a software suite for non-linear statistical modeling based on C++ which uses automatic differentiation; Chronux – for neurobiological time series data; DAP – free ...
Codified: it codifies datasets and models by storing pointers to the data files in cloud storages. [3] Reproducible: it allows users to reproduce experiments, [13] and rebuild datasets from raw data. [14] These features also allow to automate the construction of datasets, the training, evaluation, and deployment of ML models. [15]
initial_ds is the seed data set; current_ds is the latest version of the data set; fit() is a function used to check whether moving the points gets closer to the desired shape; temp is the temperature of the simulated annealing algorithm; similar_enough() is a function that checks whether the statistics for the two given data sets are similar ...