Small Data Lab 🝰

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Technologies To The People Small Data Art Analytic Project ☉

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Inventing The Future Of Art Data Analytics


🜨 Outline a new approach to descriptive art analytics using CCU CGG CGG GCA’s database of artists’ completes works.

🜨 Chart a never-before seen view of artist’ full body of work.

🜨 Predictive analytics using a random forest machine learning model.

Algorithm realRatingMatrix

recommendation_artist <- recommenderRegistry $get_entries(dataType = "realRatingMatrix") names(recommendation_artist).

Searching for microdata

LMicrodata connects people with useful insights, meaningful, organized and stored –often visually– to be accessible and understandable for everyday tasks   

Kruskal’s Algorithm for finding

mis at most n2 and log n2 = 2logn es O(log n)

Greedy algorithm. Algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a greedy strategy does not usually produce an optimal solution, but nonetheless, a greedy heuristic may yield locally optimal solutions that approximate a globally optimal solution in a reasonable amount of time.

Dijkstra's dinamic search

O((|A|+|V|) log |V|) = O(|A| log |V|) 

Having a weighted directed graph of N N non-isolated nodes, let x x x be the initial node. A vector D D of size N N will store at the end of the algorithm the distances from x x to the other nodes.

Greedy Triangulation

( C ← C ∖ { x } )  O(n . log n)

Given a finite set of inputs C, the voracious algorithm returns a set S (selected) such that S ⊆ C It also satisfies the restrictions of the initial problem. Each set S that satisfies the restrictions is usually called promising, and if it also achieves that the targeted function is minimized or maximized (as appropriate), we will say that S is an optimal solution.

Quadratic assignment

Let n be the number of facilities and locations. In turn, let N indicate the arrangement N = { 1 , 2 , . . . , n }

The quadratic assignment problem (QAP) is a standard problem in location theory. It involves assigning N facilities to a N number of sites or locations where to each of the allocations an associated cost needs to be considered. This cost will depend on the distance and flow between facilities, plus an additional cost for installing a facility in a specific location. In this way, the cost will be minimized according to distance and flow..

Data Sources 🝫

Access to our relational databases.