# Model ranked low....predictions CSV comparison?

**URL:** <https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610>\
**Category:** Tournament\
**Created:** [February 8, 2021, 5:43pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610 "2021-02-08T17:43:16Z")\
**Posts on this page:** 6\
**Page:** 1

<div class="post-metadata">

**Author:** ![goldnumberone](https://avatars.discourse-cdn.com/v4/letter/g/90db22/32.png) [@goldnumberone](https://forum.numer.ai/u/goldnumberone)\
**Post date:** [February 8, 2021, 5:43pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/1 "2021-02-08T17:43:16Z")

</div>

I submitted a model and was ranked very low; I see a lot of other people that have tied at that rank so I’m wondering if there’s a fundamental problem with the submitted predictions CSV.

Can someone in a higher rank share one of their older predictions CSV files? Or is there an example I can look at on the Numerai site?

---

<div class="post-metadata">

**Author:** ![arbitrage](https://yyz1.discourse-cdn.com/flex009/user_avatar/forum.numer.ai/arbitrage/32/2538_2.png) [@arbitrage](https://forum.numer.ai/u/arbitrage)\
**Post date:** [February 8, 2021, 5:45pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/2 "2021-02-08T17:45:33Z")

</div>

you can download the example predictions and compare. the corresponding model is numer.ai/integration\_test

---

<div class="post-metadata">

**Author:** ![wigglemuse](https://yyz1.discourse-cdn.com/flex009/user_avatar/forum.numer.ai/wigglemuse/32/3582_2.png) [@wigglemuse](https://forum.numer.ai/u/wigglemuse)\
**Post date:** [February 8, 2021, 6:11pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/3 "2021-02-08T18:11:38Z")

</div>

Can you clarify what you are talking about? Your leaderboard rank is cumulative over 20 rounds, so when someone submits for the first time they will always have a horrible rank because it takes time to build it up. (Even if you are doing awesome on the round you submitted.)

---

<div class="post-metadata">

**Author:** ![goldnumberone](https://avatars.discourse-cdn.com/v4/letter/g/90db22/32.png) [@goldnumberone](https://forum.numer.ai/u/goldnumberone)\
**Post date:** [February 8, 2021, 6:16pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/4 "2021-02-08T18:16:02Z")

</div>

I was wondering if my predictions CSV had errors in it that would cause low rankings but what you said makes sense, it’ll build up rank over time.

Though I did discover issues when comparing my predictions CSV to the example predictions; my submission has far less precision (0.25 instead of 0.2499 for example).

---

<div class="post-metadata">

**Author:** ![wigglemuse](https://yyz1.discourse-cdn.com/flex009/user_avatar/forum.numer.ai/wigglemuse/32/3582_2.png) [@wigglemuse](https://forum.numer.ai/u/wigglemuse)\
**Post date:** [February 8, 2021, 6:26pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/5 "2021-02-08T18:26:51Z")

</div>

Yeah, you should avoid ties in your predictions as much as possible, i.e. try to have all unique values. (Even though there are only 5 target values because of the way we are scored it is best not to have ties.) So more precision is good – go for that.

---

<div class="post-metadata">

**Author:** ![goldnumberone](https://avatars.discourse-cdn.com/v4/letter/g/90db22/32.png) [@goldnumberone](https://forum.numer.ai/u/goldnumberone)\
**Post date:** [February 8, 2021, 8:07pm UTC](https://forum.numer.ai/t/model-ranked-low-predictions-csv-comparison/1610/6 "2021-02-08T20:07:45Z")

</div>

Awesome, looks like I had an issue within my machine learning code and was copying over the wrong column.

Looks like this now 😃

```auto
id,prediction_kazutsugi
n0003aa52cab36c2,0.46591565012931824
n000920ed083903f,0.4782555401325226
n0038e640522c4a6,0.5369644165039062
n004ac94a87dc54b,0.48990345001220703 

```

Just submitted to make sure it validates and it looks good.

Thanks for the help!
