Questions tagged [xor-problem]
For questions related to the XOR problem, i.e. the problem of computing/approximating the XOR logical function, i.e. a function $f: \{0, 1\}^2 \rightarrow \{0, 1\} $ that returns 1 only when the two bits are different and 0 otherwise, i.e. $f(a, b) = 1 \iff a \neq b$ and $a, b \in \{0, 1\}$.
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Bug in backpropagation algorithm
I've been debugging my backpropagation algorithm for nearly a week and I can't seem to find where I went wrong, yet my network doesn't seem to learn correctly. It learns XOR just fine when I use the ...
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Why does this neural network require 2 hidden layers to completely fit my data?
I have been working toward implementing my own Neural Network library in C++ for fun.
I have managed to implement an XOR solving network based on widely available information. Now, I wanted to try a ...
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Did the unsolved XOR problem in "Perceptrons: An Introduction to Computational Geometry" 1969 book really cause the winter of the AI in 1974?
Winter of AI definition:
periods of reduced funding and interest in artificial intelligence research, due to unmet expectations after a period of hype. There have been at least two major AI winters ...
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Why does my neural network to solve the XOR problem always output 0.5?
I'm trying to create a neural network to simulate an XOR gate.
Here's my dataset:
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Is there a proof to explain why XOR cannot be linearly separable?
Can someone explain to me with a proof or example why you can't linearly separate XOR (and therefore need a neural network, the context I'm looking at it in)?
I understand why it's not linearly ...
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Can XGBoost solve XOR problem?
I've read that decision trees are able to solve XOR operation so I conclude that XGBoost algorithm can solve it as well.
But my tests on the datasets (datasets that should be highly "xor-ish"...
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What is the simplest classification problem which cannot be solved by a perceptron?
What is the simplest classification problem which cannot be solved by a perceptron (that is a single-layered feed-forward neural network, with no hidden layers and step activation function), but it ...
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Which part of "Perceptrons: An Introduction to Computational Geometry" tells that a perceptron cannot solve the XOR problem?
In the book "Perceptrons: An Introduction to Computational Geometry" by Minsky and Papert (1969), which part of this book tells that a single-layer perceptron could not solve the XOR problem?
I have ...
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If we use a perceptron with a non-monotonic activation function, can it solve the XOR problem?
I found several papers about how to build a perceptron able to solve the XOR problem. The papers describe a solution where the heaviside step function is replaced by a non-monotonic activation ...
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Why can't the XOR linear inseparability problem be solved with one perceptron like this?
Consider a perceptron where $w_0=1$ and $w_1=1$:
Now, suppose that we use the following activation function
\begin{align}
f(x)=
\begin{cases}
1, \text{ if }x =1\\
0, \text{ otherwise}
\end{cases}
\...
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What is the best XOR neural network configuration out there in terms of low error?
I'm trying to understand what would be the best neural network for implementing an XOR gate. I'm considering a neural network to be good if it can produce all the expected outcomes with the lowest ...
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Did Minsky and Papert know that multi-layer perceptrons could solve XOR?
In their famous book entitled Perceptrons: An Introduction to Computational Geometry, Minsky and Papert show that a perceptron can't solve the XOR problem. This contributed to the first AI winter, ...
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