### Show A* search is complete by example

Referring to the diagram, if we start at B and try to reach goal state E, the Lowest cost first search (LCFS) (aka Uniform cost search) algorithm fails to find a solution. This is because, B selects A over C to expand as f(A)=g(A)=36 < f(C)=g(C)=70. f(n) is the cost function of node n, and…

### How does maximum approximation of the posterior choose a distribution?

I was learning about the maximum a posteriori probability (MAP) estimation for machine learning and I found a nice short video that essentially explained it as finding a distribution and tweaking the parameters to fit the observed data in a way that makes the observations most likely (makes sense). However, in mathematical terms, how does…

### Reducing Annotation Efforts

For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have \$10,000\$ images and want to draw bounding boxes on 2 objects for each image, do we have to physically draw those boxes? Is that what most people do these days to create training data?

### Deep learning for bitmap tracing: extract simple svg paths from bitmaps

I need an algorithm to trace simple bitmaps which only contain paths with a given stroke width. It is obviously very easy to generate bitmaps from vector paths, so creating data for a machine learning algorithm is simple. Is any existing attempt to create a deep learning model which extracts vector paths from bitmaps? The…

### Decision tree implicit feature selection

I was talking with ex follow worker and he told me that the Decision tree implicitly applies a feature selection. He told me that the most important feature is higher in the tree, because the usage of information gain criteria. What does he mean with this and how does this work?

### Multi label Classification using Keras

I am trying to build a Multi label classification model, having dataset with different input numerical values and specific label… Eg: Value Label 35 X 35.8 X 29 Y 29.8 Y 39 AA 41 CB So depending on input numerical value the model should specify its label….please note that the input values won’t necessarily follow…

### Why do Bayesian algorithms work good with small datasets?

I read very often that Bayesian algoriths are working good on small datasets why is that? (I think it is because it is good at generalizing, but why is that?) https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=7636&context=etd https://math.stackexchange.com/questions/2589224/how-is-bayesian-inference-better-than-classical-inference-on-small-samples What is the reason why Bayesian works good at small datasets?

### How does the neural-network know how to tweak weights for a specific neuron?

I know backpropagation uses cost and gradient descent to tweak the weights to minimize the cost. But how does it know which weights to give more weight to in the first place? Is there something inside each neuron in the hidden layers that defines how this is an important neuron for the correct result in…

### create a minimization function

I am not sure if I am in the right place but I am trying to find some infos or tutorial in one of my problem and I do not know where to look at or how this is call to help me in my research… I am a variable, let’s say it’s a grade…

### Neural network is not giving the expected output after training in Python

My neural network is not giving the expected output after training in Python. Is there any error in the code? Is there any way to reduce the mean squared error (MSE)? I tried to train (Run the program) the network repeatedly but it is not learning, instead it is giving the same MSE and output.…