What type of ML algorithm / model should I use for prediction? : <p>I apologize this might be a poorly asked question, Im looking for more of a point in the right direction to start research. </p>

<p>So say I have large sets of Array data. Ill be easiest to give an example:</p>

<pre><code>[{a: 1}, {h: 3}, {r:7}, {p: 2}] 
[{y: 4}, {p: 3}, {w: -3}, {u: 54}]
[{l: -9}, {h: 5}, {r: 9}, {p: 5}]
[{o: -5}, {f: 4}, {i: 0}, {t: 1}]
[{a: 1}, {h: 2}, {r:5}, {p: 2}] 
</code></pre>

<p>Okay so the keys of the objects doesn't really matter. What I want to be able to do is train a model on these objects by saying which list is 'good' and which list is 'bad'. From the example data above, if the 1st , 3rd, 5th list is 'good' and the 2nd and 4th are 'bad' I want the model to be able to identify that they all share the similar factors of h, r, p, that h, r, p are positive value (or negative or something of that form), and that they are in the same order in the list. so for example if I were to pass in <code>[{h: 2}, {a: 1}, {p: 2}, {r:5}]</code> as bad I would be able to separate it out as a different order. So basically I want to be able to identify what is most likely to results in a 'good' list be comparing similarities.</p>
