Creating Machine Learning Classifier Feature Sets - Python for Finance 15

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In this tutorial, we discuss how we're going to build our feature sets for our machine learning trading algorithm.

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You Sir, are a good teacher. Thank you for these videos. This has been very enlightening.

alexwhb

I thought I had an error in the code at first, the print in the log was all 'nan'. But I changed the backtest start time to the same as you used and not the default, then it was all good.

Thanks for great videos and sharing knowledge!

leidefeldt

Hi Harrison,
Really stuck on visualizing this part: 2:00 min
while bar < len(price_list)-1:
Is price_list length -1 the end of the list but before the last element?
Could you give examples?

biffysix

What does the "bar" refer to (in this context)?
I think I am pretty much familiar with finance terminologies, but I don't know this one.

hideyukifukui

Dear Sir,

I little bit confuse with this statement
features = / pricing_list[:-1] * 100.0, 1)
why you divide with pricing_list[-1] # the last value of pricing list, not the whole pricing list ?

Thx

liminm

I am getting the below error I think this is because of changes in Quantopian 2 can you please advise ?

UnboundLocalError: local variable 'price' referenced before assignment
...
USER ALGORITHM:28, in handle_data
price_list = price[stock].tolist()

DurgeshSakhardande

Harrison, in your for loop you can just use "i" in place of "_" and get rid of the xx variable.

for i in
price = price_list[bar - (context.freature_window - i)]
(...)

gcm

Whenever I run this and check my logs I always get "PRINT('feature creation', 'list index out of range')" what happened I did the same thing as you sentdex

Lt.Hammer

Hi SentDex,
I keep having execution timeout error on my MacAir? Would u have any idea on this prob?

tczx

hi Sentdex, this snippet produces features in a vectorised way, no need to double looping, and in my case it is much quicker to run. Please let me know your comments.
Tx,
PP

for s in context.stocks:
if data.can_trade(s): #always perform this check!
#100 days

price_list=[]
for k in np.arange(10)]
price_df=pd.concat(price_list, axis=1)
price_df1=pd.concat([pd.DataFrame(np.around(100.0*(price_df.ix[:, k]/price_df.ix[:, 0] -1), 1)) for k in np.arange(10)], axis=1)
print(price_df1.head())

pietrop

Build error:
Line: --
Type: Error
Details: Execution timeout.
How i can repair that error?

adamfatyga

Hi sir, Your videos are awesome! but I can not find your code in this video, can you upload your code to a web or just simply put them down in the comments, I really need it! thank you a lot!

arthurananda

Creating Machine Learning Classifier Feature Sets - Python for Finance 15

Creating Machine Learning Classifier Feature Sets - Python for Finance 15

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