Argmax is a mathematical function that you may encounter in applied machine learning.
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For example, you may see “argmax” or “arg max” used in a retìm kiếm paper used khổng lồ describe an algorithm. You may also be instructed to lớn use the argmax function in your algorithm implementation.
This may be the first time that you encounter the argmax function and you may wonder what it is & how it works.
In this tutorial, you will discover the argmax function and how it is used in machine learning.
After completing this tutorial, you will know:
Argmax is an operation that finds the argument that gives the maximum value from a target function.Argmax is most commonly used in machine learning for finding the class with the largest predicted probability.Argmax can be implemented manually, although the argmax() NumPy function is preferred in practice.Kick-start your project with my new book Linear Algebra for Machine Learning, including step-by-step tutorials & the Python thả source code files for all examples.
Let’s get started.

What Is argmax in Machine Learning?Phokhổng lồ by Bernard Spragg. NZ, some rights reserved.
Tutorial Overview
This tutorial is divided into three parts; they are:
What Is Argmax?How Is Argmax Used in Machine Learning?How lớn Implement Argmax in PythonWhat Is Argmax?
Argmax is a mathematical function.
It is typically applied to another function that takes an argument. For example, given a function g() that takes the argument x, the argmax operation of that function would be described as follows:
result = argmax(g(x))The argmax function returns the argument or arguments (arg) for the target function that returns the maximum (max) value from the target function.
Consider the example where g(x) is calculated as the square of the x value and the tên miền or extent of đầu vào values (x) is limited khổng lồ integers from 1 to lớn 5:
g(1) = 1^2 = 1g(2) = 2^2 = 4g(3) = 3^2 = 9g(4) = 4^2 = 16g(5) = 5^2 = 25We can intuitively see that the argmax for the function g(x) is 5.
That is, the argument (x) lớn the target function g() that results in the largest value from the target function (25) is 5. Argmax provides a shorthvà for specifying this argument in an abstract way without knowing what the value might be in a specific case.
argmax(g(x)) = 5lưu ý that this is not the max() of the values returned from function. This would be 25.
It is also not the max() of the arguments, although in this case the argmax và max of the arguments is the same, e.g. 5. The argmax() is 5 because g returns the largest value (25) when 5 is provided, not because 5 is the largest argument.
Typically, “argmax” is written as two separate words, e.g. “arg max“. For example:
result = arg max(g(x))It is also comtháng lớn use the arg max function as an operation without brackets surrounding the target function. This is often how you will see the operation written and used in a research paper or textbook. For example:
result = arg max g(x)You can also use a similar operation to lớn find the arguments lớn the target function that result in the minimum value from the target function, called argmin or “arg min.”
How Is Argmax Used in Machine Learning?
The argmax function is used throughout the field of mathematics và machine learning.
Nevertheless, there are specific situations where you will see argmax used in applied machine learning và may need to implement it yourself.
The most common situation for using argmax that you will encounter in applied machine learning is in finding the index of an array that results in the largest value.
Regọi that an array is a danh sách or vector of numbers.
It is comtháng for multi-class classification models khổng lồ predict a vector of probabilities (or probability-like values), with one probability for each class label. The probabilities represent the likelihood that a sample belongs khổng lồ each of the class labels.
The predicted probabilities are ordered such that the predicted probability at index 0 belongs lớn the first class, the predicted probability at index 1 belongs lớn the second class, và so on.
Often, a single class label prediction is required from a phối of predicted probabilities for a multi-class classification problem.
This conversion from a vector of predicted probabilities to lớn a class label is most often described using the argmax operation và most often implemented using the argmax function.
Let’s make this concrete with an example.
Consider a multi-class classification problem with three classes: “red“, “blue,” and “green.” The class labels are mapped khổng lồ integer values for modeling, as follows:
red = 0blue = 1green = 2Each class label integer values maps khổng lồ an index of a 3-element vector that may be predicted by a model specifying the likelihood that an example belongs to lớn each class.
Consider a mã sản phẩm has made one prediction for an input sample và predicted the following vector of probabilities:
yhat = <0.4, 0.5, 0.1>We can see that the example has a 40 percent probability of belonging to lớn red, a 50 percent probability of belonging to lớn blue, và a 10 percent probability of belonging to lớn green.
We can apply the argmax function khổng lồ the vector of probabilities. The vector is the function, the output of the function is the probabilities, & the đầu vào to the function is a vector element index or an array index.
arg max yhatWe can intuitively see that in this case, the argmax of the vector of predicted probabilities (yhat) is 1, as the probability at array index 1 is the largest value.
cảnh báo that this is not the max() of the probabilities, which would be 0.5. Also note that this is not the max of the arguments, which would be 2. Instead it is the argument that results in the maximum value, e.g. 1 that results in 0.5.
arg max yhat = 1We can then maps this integer value bachồng to lớn a class label, which would be “blue.”
arg max yhat = “blue”How lớn Implement Argmax in Python
The argmax function can be implemented in Pynhỏ for a given vector of numbers.
Argmax from Scratch
First, we can define a function called argmax() that enumerates a provided vector và returns the index with the largest value.