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@@ -2,7 +2,7 @@
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name = "smartcore"
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name = "smartcore"
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description = "Machine Learning in Rust."
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description = "Machine Learning in Rust."
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homepage = "https://smartcorelib.org"
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homepage = "https://smartcorelib.org"
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version = "0.4.5"
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version = "0.4.6"
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authors = ["smartcore Developers"]
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authors = ["smartcore Developers"]
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edition = "2021"
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edition = "2021"
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license = "Apache-2.0"
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license = "Apache-2.0"
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@@ -1,4 +1,4 @@
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#![allow(clippy::ptr_arg)]
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#![allow(clippy::ptr_arg, clippy::needless_range_loop)]
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//! # Nearest Neighbors Search Algorithms and Data Structures
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//! # Nearest Neighbors Search Algorithms and Data Structures
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//!
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//!
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//! Nearest neighbor search is a basic computational tool that is particularly relevant to machine learning,
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//! Nearest neighbor search is a basic computational tool that is particularly relevant to machine learning,
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@@ -1,3 +1,4 @@
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#![allow(clippy::ptr_arg, clippy::needless_range_loop)]
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//! # Clustering
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//! # Clustering
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//!
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//!
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//! Clustering is the type of unsupervised learning where you divide the population or data points into a number of groups such that data points in the same groups
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//! Clustering is the type of unsupervised learning where you divide the population or data points into a number of groups such that data points in the same groups
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@@ -1,3 +1,4 @@
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#![allow(clippy::ptr_arg, clippy::needless_range_loop)]
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//! Datasets
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//! Datasets
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//!
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//!
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//! In this module you will find small datasets that are used in `smartcore` mostly for demonstration purposes.
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//! In this module you will find small datasets that are used in `smartcore` mostly for demonstration purposes.
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@@ -385,7 +385,7 @@ impl<T: Debug + Display + Copy + Sized> Array<T, (usize, usize)> for DenseMatrix
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}
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}
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fn is_empty(&self) -> bool {
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fn is_empty(&self) -> bool {
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self.ncols > 0 && self.nrows > 0
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self.ncols < 1 || self.nrows < 1
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}
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}
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fn iterator<'b>(&'b self, axis: u8) -> Box<dyn Iterator<Item = &'b T> + 'b> {
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fn iterator<'b>(&'b self, axis: u8) -> Box<dyn Iterator<Item = &'b T> + 'b> {
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