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ELKI contains tSNE, also with Barnes-Hut approximation; scikit-learn, a popular machine learning library in Python implements t-SNE with both exact solutions and the Barnes-Hut approximation. Tensorboard, the visualization kit associated with TensorFlow, also implements t-SNE (online version) The Julia package TSne implements t-SNE
Free replacement for SPSS. QtiPlot: GUI, Python: proprietary: No 2004: May 31, 2017 / 0.9.9.11: Linux, Mac, Windows: Python scriptable R: Third party: GPL: Yes 1993: July 2, 2018 / 3.5.1("Feather Spray") Linux, Mac, Windows: In addition to base graphics, has a large number of graphics packages including lattice and ggplot2. [7] Interoperabile ...
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A funnel plot is a scatterplot of treatment effect against a measure of study size. It is used primarily as a visual aid to detecting bias or systematic heterogeneity. Dot plot (statistics) : A dot chart or dot plot is a statistical chart consisting of group of data points plotted on a
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
The process of feature selection aims to find a suitable subset of the input variables (features, or attributes) for the task at hand.The three strategies are: the filter strategy (e.g., information gain), the wrapper strategy (e.g., accuracy-guided search), and the embedded strategy (features are added or removed while building the model based on prediction errors).
In applied statistics, a partial regression plot attempts to show the effect of adding another variable to a model that already has one or more independent variables. Partial regression plots are also referred to as added variable plots , adjusted variable plots , and individual coefficient plots .
In statistics, the Jonckheere trend test [1] (sometimes called the Jonckheere–Terpstra [2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design.