CertNexus AIP-210 Exam - Topic 7 Question 42 Discussion

Actual exam question for CertNexus's AIP-210 exam

Question #: 42
Topic #: 7

[All AIP-210 Questions]

Which of the following is NOT an activation function?

AAdditive

BHyperbolic tangent

CReLU

DSigmoid

Show Suggested Answer

Suggested Answer: A

An activation function is a function that determines the output of a neuron in a neural network based on its input. An activation function can introduce non-linearity into a neural network, which allows it to model complex and non-linear relationships between inputs and outputs. Some of the common activation functions are:

Sigmoid: A sigmoid function is a function that maps any real value to a value between 0 and 1. It has an S-shaped curve and is often used for binary classification or probability estimation.

Hyperbolic tangent: A hyperbolic tangent function is a function that maps any real value to a value between -1 and 1. It has a similar shape to the sigmoid function but is symmetric around the origin. It is often used for regression or classification problems.

ReLU: A ReLU (rectified linear unit) function is a function that maps any negative value to 0 and any positive value to itself. It has a piecewise linear shape and is often used for hidden layers in deep neural networks.

Additive is not an activation function, but rather a term that describes a property of some functions. Additive functions are functions that satisfy the condition f(x+y) = f(x) + f(y) for any x and y. Additive functions are linear functions, which means they have a constant slope and do not introduce non-linearity.

by Anjelica at May 04, 2025, 08:39 PM

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Keneth

8 months ago

I agree, A just doesn't fit with the others!

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Gwenn

8 months ago

Wait, is Additive even a thing? Sounds weird.

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Gaston

8 months ago

I thought ReLU was the go-to activation function!

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Roselle

8 months ago

Hyperbolic tangent is a common one, for sure.

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Trevor

8 months ago

A is definitely not an activation function.

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Roslyn

9 months ago

I remember practicing with activation functions, and I think Additive is the odd one out here.

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Teri

9 months ago

I'm a bit confused; I thought all of these were activation functions, but Additive sounds unfamiliar.

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Lavonda

9 months ago

I feel like I've seen a question like this before, and I'm pretty sure Sigmoid is definitely an activation function.

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Martina

9 months ago

I think I remember that the hyperbolic tangent and ReLU are both activation functions, but I'm not sure about Additive.

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Edwin

10 months ago

Activation functions are a key concept in neural networks, so I should know this. Let me quickly review the main options - Sigmoid, ReLU, tanh. Additive doesn't sound like an activation function, so I'll select A.

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Honey

10 months ago

I'm a bit unsure here. I know the common activation functions, but I can't recall if Additive is one of them. I'll have to make an educated guess and go with A.

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Melda

10 months ago

Hmm, let me think about this. Hyperbolic tangent, ReLU, and Sigmoid are all common activation functions, so I'm going to rule out those options. I'll go with A.

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Jaime

10 months ago

I'm pretty confident on this one. Additive is not an activation function, so I'll go with A.

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Geoffrey

1 year ago

I'm going to go with B. Hyperbolic tangent. That's a classic activation function, so it can't be the one that's not an activation function.

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Alayna

1 year ago

I agree, I don't think B) Hyperbolic tangent is the correct answer.

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Ryan

1 year ago

I'm leaning towards D) Sigmoid.

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Louvenia

1 year ago

I think it's A) Additive.

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Paris

1 year ago

D) Sigmoid

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Herminia

1 year ago

C) ReLU

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Dick

1 year ago

B) Hyperbolic tangent

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Delsie

1 year ago

A) Additive

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Fredric

1 year ago

I think the answer is A) Additive because it is not a commonly used activation function in neural networks.

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Selma

1 year ago

Haha, I bet the answer is C. ReLU. That's one of the most common activation functions, so it can't be the right answer here.

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Jeanice

1 year ago

You're both wrong, the correct answer is B) Hyperbolic tangent

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Brice

1 year ago

No, I believe the answer is D) Sigmoid

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Monte

1 year ago

I think it's A) Additive

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Kaitlyn

1 year ago

D) Sigmoid

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Janna

1 year ago

C) ReLU

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Arthur

1 year ago

B) Hyperbolic tangent

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Rashad

1 year ago

A) Additive

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Vincenza

1 year ago

Ooh, this one's tricky! I think the answer is A. Additive, because that's just a linear operation, not an activation function.

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Santos

1 year ago

You're right, D) Sigmoid is an activation function. The correct answer is A) Additive.

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Charlesetta

1 year ago

No, I'm pretty sure it's D) Sigmoid, that's an activation function.

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Nan

1 year ago

I think it's B) Hyperbolic tangent, because that is an activation function.

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Alecia

1 year ago

I agree, A) Additive is not an activation function.

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Maurine

1 year ago

D. Sigmoid is definitely an activation function, so that can't be the answer. Hmm, let me think...

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Brett

1 year ago

C) ReLU

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Rusty

1 year ago

B) Hyperbolic tangent

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Ryan

1 year ago

A) Additive

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Nichelle

1 year ago

But isn't hyperbolic tangent commonly used as an activation function in neural networks?

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Dan

1 year ago

I disagree, I believe the correct answer is B) Hyperbolic tangent.

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Nichelle

1 year ago

I think the answer is A) Additive.

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Kattie

1 year ago

I'm pretty sure the answer is A. Additive can't be an activation function, right?

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Vincenza

1 year ago

B) Hyperbolic tangent

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Brendan

1 year ago

No, that's incorrect. Additive is actually an activation function.

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Dorothea

1 year ago

A) Additive

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