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Home Neural Networks

Recursive Structures in Machine Learning

January 14, 2020
in Neural Networks
Recursive Structures in Machine Learning
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data tree

I do not have bachelor’s degree from computer science. Nevertheless, the structures thought in CS named as differently yet they have similar functionality. The main concept here is recursive data structures. The inheritance is recursive data structure, the child inherits the same functionality or attributes from parent. the system is recursive and repetetively the same functional program connects the parent and the child.

We know that there are data trees in computer science literatures. The constant functionalty is applied the different named objects and a tree is occured. I acknowledge the functionality over naming. The denomination is something for humans to think diversely and understand concept virtually. Nonetheless, the computers do not need such statements or conceptiality in actual. In computer science, every function and data structure is liable to recursive functionality. Therefore, we humans, can only desribe these systems from procedure literature of computer science. What I mean, we could be counted as subprograms according to literature of computer science. The computer science could be counted as subprogram of science. In summary, this can be thought such this.

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When we think like this, the universe seem simpler and graspable. Thus, the story of human that find solutions to the problems is an strorify to all our evolutionary system. Actually, we are functioning in the computational space in terms of computational science. Therefore, our functions, our subfunctions and recursive system goes through infinity or finite number of systems have always capabile some terms of data or variable in this functional system.

recursive plants maybe?

The recursion is huge concept in life not just in computer science. In reality, maybe our life is an recursive error. The life itself counters the entropy of universe and life recursively gives birth and continue the some terms of functions in the universe.

This is very deep subject. You can research on internet and grasp the ideas from reddit or somewhere. In the end, the philosophy and idealism in the mind generates the ideas to solutions. I just want to desribe how the human mind and nature interaction works. If you can understand the systematic scheme of this, you may function in the exploration area of life. Other may be is exploitation. These terms are not just phenomens of Artificial Intelligence or Computer Science… These are the mainly describing life motto like terms.

art of garbage

The perception of this picture “art of garbage” is an garbage of art. Again, this is recursive structure. An art piece together with other art pieces structures and art piece. However, this is named as garbage in the end. The “garbage” noun describes the total result, conclusion of the system. We humans could desribe this as aggregated unvalued piece of arts concentration on a geometric point in environment. You can assign null computationally these articles. Nevertheless, these could be very meaningfull, functional articles for some people.

These are creational thoughts that may help you or can intrigue your thoughts. This might lead you to background of my approach to new system.

When you understand the recursive systems, the ambiguity of the paragrahps or sentences could be less meaningfull for you.”This might lead you to background of my approach to new system.” In this sentence, I want to use approach twice. However, to enrich your attention, I used system after approach. In the hominoid sense, this will appear you as expressive sentence by historical language education. However, this sentence in functional way breaks the recursive functionality and make a loss of information in the sentence. The diverse naming could make “epsilon” differences in meanings and approximate meanings “recursively” could make huge differences in total.

The functional and hominoid world is so different from each other. As we humans, our secret desire to preserve our meaning and aliveness in such environment. That’s why there are lots of gap between truth and exhibited life of human.

In conclusion, I want to prepare you for the this concept of machine learning.

Recursive Tree

In general machine learning executions, the community until now, stand on the pattern recognition of this problem.

A → B → C → True

B → C →E →True

A →E →D →False

an so on. This is the basic of pattern recognition. In this pattern recognition, which is classification case, we try to predict the figures results true or false. However, the slots could have recursive data structures and classification also. We see that the recursive tree of target value is equal the features and features describes the target values. I should give an example to graps it further.

For example, we want to understand the human gesture, if the person smiles, we collect data from face and save it. There are numerous approach to this problem. Mainly we can collect the every face data in face. These features could be

forehead, eyes,ears,cheeks,lip,jaw,temporal. These features could have inside subfeatures. We do not know which attributes from these features belong to in relational mean. That’s why we save them in a matrix. The data structure seem like

forehead, eyes,ears,cheeks,lip,jaw,temporal — — — — — — — — — —

matrix_1,matrix_2,matrix_3,matrix_4,matrix_5,matrix_6,matrix_7 → smile

matrix_1,matrix_2,matrix_3,matrix_4,matrix_5,matrix_6,matrix_7 → not_smile

matrix_1,matrix_2,matrix_3,matrix_4,matrix_5,matrix_6,matrix_7 → not_smile

matrix_1,matrix_2,matrix_3,matrix_4,matrix_5,matrix_6,matrix_7 → smile

and so on…

The more complex is creating an tensor for result.

3D_matrix → smile

3D_matrix → not_smile

and so on…

We know that, the machine learning algorithms only understand the linear relation. Nonetheless, the versatile machine learning algorithms or transformed algorithms could understand the relations between a112 , a231 and b231. A tensor or 4D or 5D may be so complex and training could take days to complete. However, this system might understand little details in the machine learning.

Unsupervised an supervised learning could be applied to these forms of structures.

I want to describe that there could be a possible form of algorithms for 2D ++

data stuctures and I hope in the near future, the idea will be approved.

Credit: BecomingHuman By: Barış Can Tayiz

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