#PLA Lab understanding

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limber monolith
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So in my lab says make PLA with matlab but im going to use python. I just need help understanding number 2 where it says generate for 2D Plane so does this mean my input X should only have 2 characteristics in order to be 2D plane? for example of an input would be X0 (bias), X1(x-axis) and X2(y-axis)? or am I understanding wrongly?

Right now I am just generating random X inputs (coordinates) and then using a classification function to classify them as +1 or -1 and then I loop through and adjust weights to find the boundary. Just asking if that's what it is asking me to do or my X inputs can be more than just 2 features (x and y coord).

Sorry I am new to machine Learning

vagrant wedge
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most people here dont know what PLA means

raven vigil
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a 3d printing filament material

vagrant wedge
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Perceptron Learning Algorithm

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and classification of items

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Steps to generate the data:
Generate N random points in a 2D space.
Assign class labels (-1 or +1) based on a simple rule (e.g., whether they lie above or below a randomly chosen line).
Plot the points to visualize the two classes.

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chatgpt can help with most of the code

limber monolith
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yes I just need to understand Generate N random points in a 2D space part. Does this mean only 2 features/attribute/characteristic of my input being X and Y coord?

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like example an input like movie can have many characteristics (name, genre, etc) does 2D space mean my Input should only have 2 characteristics so it's easier to plot on a 2D plane?

limber monolith
vagrant wedge
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90% of people come here for help with realtime voice changer

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and to find voice models

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for the task, you have x 0 to 100 and y 0 to 100, you generate a random xy coordinate, then set the value to -1 or 1 based on where the random coordinate lies

limber monolith
vagrant wedge
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ignore the labels

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make dots above the line have value 1 (green), dots below the line have value -1 (red)