feat: add enum ml/base/cluster/kmeans/algorithms

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/README.md

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+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# Clustering Algorithms
+
+> k-means clustering algorithms.
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- Package usage documentation. -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var algorithms = require( '@stdlib/ml/base/cluster/kmeans/algorithms' );
+```
+
+#### algorithms()
+
+Returns a list of k-means clustering algorithms.
+
+```javascript
+var out = algorithms();
+// e.g., returns [ 'lloyd', 'elkan' ]
+```
+
+The output array contains the following algorithms:
+
+-   `lloyd`: classic EM-style algorithm.
+-   `elkan`: optimized algorithm using triangle inequality.
+
+</section>
+
+<!-- /.usage -->
+
+<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- Package usage examples. -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var contains = require( '@stdlib/array/base/assert/contains' ).factory;
+var algorithms = require( '@stdlib/ml/base/cluster/kmeans/algorithms' );
+
+var isAlgorithm = contains( algorithms() );
+
+var bool = isAlgorithm( 'lloyd' );
+// returns true
+
+bool = isAlgorithm( 'elkan' );
+// returns true
+
+bool = isAlgorithm( 'beep' );
+// returns false
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/ml/base/cluster/kmeans/algorithms.h"
+```
+
+#### STDLIB_ML_KMEANS_ALGORITHM
+
+An enumeration of k-means clustering algorithms with the following fields:
+
+-   **STDLIB_ML_KMEANS_LLOYD**: classic EM-style algorithm.
+-   **STDLIB_ML_KMEANS_ELKAN**: optimized algorithm using triangle inequality.
+
+```c
+#include "stdlib/ml/base/cluster/kmeans/algorithms.h"
+
+const enum STDLIB_ML_KMEANS_ALGORITHM v = STDLIB_ML_KMEANS_LLOYD;
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+### Notes
+
+-   Enumeration constants should be considered opaque values, and one should **not** rely on specific integer values.
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/benchmark/benchmark.js

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+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives;
+var pkg = require( './../package.json' ).name;
+var algorithms = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var out;
+	var i;
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = algorithms();
+		if ( out.length < 2 ) {
+			b.fail( 'should return an array' );
+		}
+	}
+	b.toc();
+	if ( !isStringArray( out ) ) {
+		b.fail( 'should return an array of strings' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/docs/repl.txt

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+
+{{alias}}()
+    Returns a list of k-means clustering algorithms.
+
+    The output array contains the following algorithms:
+
+    - lloyd: classic EM-style algorithm.
+    - elkan: optimized algorithm using triangle inequality.
+
+    Returns
+    -------
+    out: Array<string>
+        List of algorithms.
+
+    Examples
+    --------
+    > var out = {{alias}}()
+    [ 'lloyd', 'elkan' ]
+
+    See Also
+    --------
+

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/docs/types/index.d.ts

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+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Returns a list of k-means clustering algorithms.
+*
+* @returns list of clustering algorithms
+*
+* @example
+* var list = algorithms();
+* // e.g., returns [ 'lloyd', 'elkan' ]
+*/
+declare function algorithms(): Array<string>;
+
+
+// EXPORTS //
+
+export = algorithms;

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/docs/types/test.ts

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+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import algorithms = require( './index' );
+
+
+// TESTS //
+
+// The function returns an array of strings...
+{
+	algorithms(); // $ExpectType string[]
+}
+
+// The compiler throws an error if the function is provided any arguments...
+{
+	algorithms( 9 ); // $ExpectError
+}

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/examples/index.js

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+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var contains = require( '@stdlib/array/base/assert/contains' ).factory;
+var algorithms = require( './../lib' );
+
+var isAlgorithm = contains( algorithms() );
+
+var bool = isAlgorithm( 'lloyd' );
+console.log( bool );
+// => true
+
+bool = isAlgorithm( 'elkan' );
+console.log( bool );
+// => true
+
+bool = isAlgorithm( 'beep' );
+console.log( bool );
+// => false

lib/node_modules/@stdlib/ml/base/cluster/kmeans/algorithms/include/stdlib/ml/base/cluster/kmeans/algorithms.h

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+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_ML_BASE_CLUSTER_KMEANS_ALGORITHMS_H
+#define STDLIB_ML_BASE_CLUSTER_KMEANS_ALGORITHMS_H
+
+/**
+* Enumeration of k-means clustering algorithms.
+*/
+enum STDLIB_ML_KMEANS_ALGORITHMS {
+	// Classic EM-style algorithm:
+	STDLIB_ML_KMEANS_LLOYD = 0,
+
+	// Optimized algorithm using triangle inequality:
+	STDLIB_ML_KMEANS_ELKAN,
+};
+
+#endif // !STDLIB_ML_BASE_CLUSTER_KMEANS_ALGORITHMS_H