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

6 months ago

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

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Gwenn

6 months ago

Wait, is Additive even a thing? Sounds weird.

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Gaston

6 months ago

I thought ReLU was the go-to activation function!

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Roselle

6 months ago

Hyperbolic tangent is a common one, for sure.

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Trevor

7 months ago

A is definitely not an activation function.

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Roslyn

7 months ago

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

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Teri

7 months ago

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

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Lavonda

7 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

7 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

8 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

8 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

8 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

8 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

12 months 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

11 months ago

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

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Ryan

11 months ago

I'm leaning towards D) Sigmoid.

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Louvenia

11 months ago

I think it's A) Additive.

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Paris

11 months ago

D) Sigmoid

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Herminia

11 months ago

C) ReLU

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Dick

11 months ago

B) Hyperbolic tangent

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Delsie

11 months 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

11 months ago

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

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Brice

11 months ago

No, I believe the answer is D) Sigmoid

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Monte

11 months ago

I think it's A) Additive

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Kaitlyn

12 months ago

D) Sigmoid

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Janna

12 months 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

11 months ago

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

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Charlesetta

12 months ago

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

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Nan

12 months 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

12 months ago

C) ReLU

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Rusty

12 months 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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