How can I calculate and cluster the Risk percentage and clustering them if the only details available is Profit per customer and number or orders?
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The owner of the store observes that, on average, 18 customers enter every hour, and that there are typically 8 customers in the store. How much time does each customer spend in the store on average?
How to relate to the formula t = n*CPI/f?
I'm playing a little with spot instances, and for example, in Databricks, I can ask for a spot instance with a minimum of % savings over On-Demand instances.
My question is, if I set 90% off the On-Demand instance and the current price is 50%, I will get the cheaper instance or is it like bidding and I get the spot for 90% price?
I have some use cases when the availability of one instance is not very important so will be good to get those at any discount.
Summing up, if I set a minimum of 90% I will always get the cheaper spot available?
Thanks!
As per the this article from databricks:
Databricks defaults to a bid price that is equal to the current on-demand price. So if the on-demand price for your instance type is $0.665 cents per hour, then the default bid price is also set to $0.665 cents per hour.
Recall that with Spot instances, you don’t necessarily pay your actual bid price - you pay the Spot market price for your instance type. So, even though you may have bid $0.665 cents, in reality you may only be charged $0.10 for the hour.
So its safe to assume that you will be charged whats the current spot market price but not more then what you set.
I manage the advertising campaigns of some clients with fixed monthly budgets. I'm trying to create a formula that will (a)show how their budget is pacing based on the amount they have spent vs the month elapsed. And (b) if they are overpacing on their monthly budget, what do they need to increase their monthly budget to in order to maintain their current pace of spend. Any help would be much appreciated :)
Unsure how the cost per share is calculated for an entire account. I've tried taking the Total Cost Basis / Billing Market Value, but that did not produce the same number that is showing. I've tried adding up all of the cost per shares for the lots held within the account and divided by the number of lots, but that also did not work.
Cost per share or "Cost Basis Per Unit" is calculated as the Cost Basis (with or without amortization based on settings) divided by the number of units in the lot.
Assume i have a list of newspaper subscribers and their geographical location (f.e. postal codes) and the distance between different locations.
The goal is cluster subscribers together in 'rounds'. The size/length of a round is constrained by time: there is only limited time available for delivery each morning. This limits maximum distance per round.
Is their an algorithm that allows me to cluster subscribers/addresses into 'rounds' in such a manner that I minimise the number of required paperboys/rounds?