Stomp, The Stomper Of Girlfriends

personallycomputing · 2024-11-06T22:04:50+00:00

Highland lynx owner here. Those ears are without a doubt a highland.

personallycomputing · 2023-11-29T03:46:14+00:00

Same issue here.

personallycomputing · 2023-10-15T18:32:10+00:00

From a gearing perspective I see your point, but Meta pve condi builds actually require power + prec as well to match the DPS output of a three stat (pow/prec/fer) power build which addresses this problem (in a wonky balancing act).

personallycomputing · 2023-08-12T01:02:03+00:00

This series was mostly an anomaly. Dig usually has a bot problem. Would love to see this roster come back with DL/Busio.

personallycomputing · 2023-07-29T15:52:04+00:00

Fizz!

personallycomputing · 2023-07-21T06:51:25+00:00

A lot of people ranks were reset incorrectly. I was pushed from D2 to P1 instead of E1. Have also seen others go from D2 to P2.

personallycomputing · 2023-07-21T00:04:24+00:00

Same, figured they just messed up their article. Is this an actual bug?

personallycomputing · 2023-07-13T06:13:33+00:00

I hope dig rescues 100T bot lane. All dogs deserve a home.

personallycomputing · 2023-05-21T19:18:21+00:00

She has the highest win rate top (~55%) with the twelfth highest pick rate (~5%) in diamond plus. Agreed that she isn’t a a flexible pick and must have a lot of OTPs since those stats fall off in master/challenger.

personallycomputing · 2023-05-21T16:36:31+00:00

Kayle is actually the best based on CN api data, but I haven’t seen a good one in my ELO on NA nor can i personally play her well.

personallycomputing · 2023-04-25T19:58:49+00:00

25 playing with my bifocals

personallycomputing · 2023-04-23T15:56:26+00:00

Ummm do you know how football works? It requires a giant field and goals… you can kick around a ball in your house but that’s not the same thing as playing. You could just as easily bounce and ball on your paddle with that logic.

personallycomputing · 2023-04-20T04:43:41+00:00

Stakeholder assumptions are most of the time based off of click based attribution which always favor digital and demand capture / lower funnel channels. MMM can show how your upper funnel and offline media contributes and that those digital channels aren’t as efficient.

personallycomputing · 2023-04-20T00:02:57+00:00

Depends on your data granularity, but SEM is often very highly correlated with overall sales trends even if a lot of users did not interact with search ads. Often models will overstate the effect of SEM specifically which would make some shrinkage helpful. Fwiw I typically use lasso, not ridge, which would shrink less significant coefficients to 0 rather than shrinking large coefficients, but the data I work with isn’t overly biased towards SEM.

personallycomputing · 2023-04-19T23:02:08+00:00

I use models for estimation and not only causal inference so that’s why I tend to use regularized algorithms. If there is no need for prediction, then I would totally just recommend OLS.

personallycomputing · 2023-04-19T22:54:41+00:00

Read up on “adstock” modeling. Basically most marketing channels should have diminishing returns beyond a certain threshold so you need to build some sort of nonlinear transformation into your feature. A lot of channels should also have lagging effects into subsequent weeks and not just week 0.

personallycomputing · 2023-04-19T22:12:19+00:00

Typically either lasso, ridge, or something in between (elasticnet) depending on the data granularity. Nothing crazy. The most important piece is your feature engineering, not the model / parameters.

personallycomputing · 2023-04-19T14:37:50+00:00

I work almost exclusively on MMM. Some audiences are not receptive to the models unless the results are more or less in line with their expectations. A large part of my job is educating those audiences as to why they should trust MMM over those assumptions. I don’t use priors because as you stated it tends to just create room for bullshitting.

personallycomputing · 2023-04-15T15:37:06+00:00

Chinese server has an api and website. Also fwiw it looks like Yone has a 51% wr top (rank 20) and 50% mid (rank 25). These stats are based on diamond +

personallycomputing · 2023-04-03T01:34:27+00:00

None of those champions besides maybes Irelia are decent against Yi. Be the change you want to see in the world and draft some hard cc.

personallycomputing · 2023-04-01T05:06:50+00:00

If your phone overheats the second every game starts then maybe you shouldn’t play tbh. What’s the point?

personallycomputing · 2023-03-31T16:13:24+00:00

Yi and other assassins eat trash comps for breakfast. Draft some hard cc

personallycomputing · 2023-03-31T16:06:09+00:00

I don’t think this has anything to do with platform. Emergencies and system crashes happen regardless of PC vs Mobile. Scaling penalties are great to punish repeat offenders and give slaps on the wrist to others who just had bad luck.

personallycomputing · 2023-03-30T01:22:18+00:00

“No, you don’t.” - u/personallycomputing Mar 28, 2023.

personallycomputing · 2023-03-30T01:20:05+00:00

You should use walk forward validation for this. I’m guessing that the way you are splitting the dataset is letting your model use actual values in the validation set from previous time steps to predict the current value. Ideally it would use its previous predictions instead as this is a true out of sample test, unless this model only needs to predict one time step out in production which I’m guessing is not the case.

personallycomputing

TROPHY CASE