Standard library incremental machine learning algorithms.
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Support the dependencies of stdlib-js/ml-incr
Incrementally perform binary classification using stochastic gradient descent (SGD).
Incrementally partition data into `k` clusters.
Define a read-only property.
Float64Array.
Test if an array-like value contains a search value.
Test if an object has a specified property.
Test if a value is an array.
Test if a value is an array-like object.
Test if a value is a boolean.
Check if the runtime is a web browser.
Test if a value is a function.
Test if a value is ndarray-like.
Test if a value is a number having a nonnegative value.
Test if a value is a number.
Test if a value is a plain object.
Test if a value is a number having a positive integer value.
Test if a value is a number having a positive value.
Test if a value is a string.
Copy values from x into y.
Double-precision floating-point positive infinity.
Round a double-precision floating-point number toward negative infinity.
Evaluate the natural logarithm of a double-precision floating-point number.
Return the maximum value.
Exponential function.
Compute the principal square root of a double-precision floating-point number.
Multidimensional arrays.
Base multidimensional array.
Return the number of elements in an array.
Generate a stride array from an array shape.
Multidimensional array constructor.
Discrete uniform distributed pseudorandom numbers.
A linear congruential pseudorandom number generator (LCG) whose output is shuffled.
A 32-bit Mersenne Twister pseudorandom number generator.
Uniformly distributed pseudorandom numbers between 0 and 1.
Online regression via stochastic gradient descent (SGD).
Int8Array.
Test if a value is a 2-dimensional ndarray-like object.
Test if a value is a 1-dimensional ndarray-like object.
Copy values from x into y.
Multiply a double-precision floating-point vector by a constant.
Multiply x by a constant and add the result to y.
Calculate the dot product of two vectors.
Natural exponential function.
Standard logistic function.
Convert a linear index in an array view to a linear index in an underlying data buffer.
Plotting.
Binomial distributed pseudorandom numbers.
Normally distributed pseudorandom numbers.
Compute an arithmetic mean incrementally.
Sample elements from an array-like object.
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