Numerade

Questions asked

INSTANT ANSWER

Quention 3 Normalius the row of the input matris to hwe the \( L_{\text {a }} \) nare equal to 1, we the cade ecarple belew. Without that nsmelivation, ovwrfow errors might accur in the exponemiol function? step aise is taken from a lat \( [0.1, \ldots, 1.0] \) we the Pyitan cade below. "Pythen import numpy wn np fram akbarndatasets impart laad brent_cancer fram sklearn-adel_whetan import KI ald fram skbarn-etrica impart rac_we,acore allad the data mdaka ndie - Xshape Af ta comert the \( \{0,1] \) autput ints \( [-1,+1\} \) \( y=2^{2} y-1 \) AS hyperparameten of the barning tank of Q-ention I wh lint of step wices Ieta \( -|0.1 *| j+1 \mid \) for \( i \) in range(10) us number of iteration iteratan \( = \) sa nfold os of number af folds np. tandam wesd(12345) si fox the randam weed to avad randar flectuation of the results As te pitt the data into S-foids we mend As normaluatio- Af acalng the nows by raximum abuatute val Le, \( L \) infinite narm af columex MDC curve, w an acruracy memuse on the carrapending validation wet. Hound the mumbers up to 2 decimal plecks and select the closest ene from the pusible amanen. a. \( 0.24,0.6 \) b. Oas, a.1 \( \mathrm{O} c \) ontas 0 d. 0.91, a.s

View Answer

ANSWERED

Rachel Gore

Numerade educator

Question 2 In applying the Perceptron algorithm on a data set, {(X_i, y_i)}_{i=1}^m where y_i ? {?1, +1}, ?i, we might normalize all input vectors X with the largest absolute value of the input components. In vectorized Numpy form we have that: xnorm = np.max(np.abs(X)); X = X / xnorm where X is a matrix containing the input vectors in its rows. It is assumed that the margin ? is the largest value satisfying y_i w_* · x_i ? ? for all i = 1, ..., m. Question: what is the effect of this type of normalization? Assume that the two classes are linearly separable, and no bias term is included into the predictor function. In the questions, the expected number of iteration is denoted by t in the last item of Novikoff's theorem on the corresponding slide. Select that answer which is true if this kind of normalization is applied! a. The normalization does not change the weight vector w. b. In the Novikoff's Theorem, the number of expected iterations does not depend on this type of normalization. c. In the Novikoff's Theorem, the number of expected iterations increases when xnorm > 1. d. In the Novikoff's Theorem, the number of expected iterations decreases when xnorm > 1.

View Answer

INSTANT ANSWER

Question 1 P Flag question Marked out of \( 1.0 \quad \) Nat yet answered between \( x \) and \( y \). \[ \begin{array}{l} \operatorname{Pr}(1 \mid x)=\left\{\begin{array}{ll} +h x+h & \text { if } x \in[-1,0], \\ -h x+h & \text { if } x \in[0,+1], \end{array}\right. \\ \operatorname{Pr}(0 \mid x)=1-\operatorname{Pr}(1 \mid x)=\left\{\begin{array}{ll} -h x+1-h & \text { if } x \in[-1,0], \\ +h x+1-h & \text { if } x \in[0,+1], \end{array}\right. \end{array} \] where \( h=0.75 \). Assume that \( x \) has a uniform distribution on \( [-1,1] \). The question: What is the value of the Bayes error if \( h=0.75 \) ? Hint: You might solve this problem by computing the integral \[ \int_{-1}^{+1} \min (\operatorname{Pr}(1 \mid x), \operatorname{Pr}(0 \mid x)) p(x) d x \] where \( p(x) \) is the density function of the variable \( \boldsymbol{x} \), or by considering the shape of the minimum function. a. \( \log (2) \) b. 0.5123 c. 0.2917 d. \( 1 / \sqrt{2} \)

View Answer

ANSWERED

Lottie Adams

Numerade educator

How do I calculate this on Excel? Analyze whether higher discounts result in higher sales. Calculate the correlation between discount percentages and sales.

View Answer

ANSWERED

Nick Johnson

Numerade educator

Compare attribution modeling and MMM as analytical methods and sources of information for marketing managers. Write about 200-250 words essay.

View Answer

INSTANT ANSWER

Reflecting on Wedel&Kannan(2016) Marketing Analytics for Data-Rich Environments, discuss Excel as a tool for analysis in modern data-rich marketing environments. Write roughly 200 words in a professional format.

View Answer

INSTANT ANSWER

December results: TOTAL CONVERTED: Facebook Ads 500 googleadwords_int 780 ironsource_int 239 unityads_int 4 vungle_int 140 COST PER PURCHASE: Facebook Ads 81,07 € googleadwords_int 51,97 € ironsource_int 169,61 € unityads_int 10 134,17 € vungle_int 289,55 € How would you allocate budgets between the media sources based December 2021 results? Which channels you would scale up and which down? What would be your main metrics when making these decision?

View Answer

INSTANT ANSWER

I have data with these columns: media_source acquisition_date cost Impressions clicks Installs d0_to_d1_iap_revenue_usd d0_to_d3_iap_revenue_usd d0_to_d7_iap_revenue_usd d0_to_d30_iap_revenue_usd d1_retained d3_retained d7_retained d30_retained d0_to_d1_converted d0_to_d3_converted d0_to_d7_converted d0_to_d30_converted. I need to calculate the D30 ROI of Q4 in 2021, Which media sources had the highest / lowest D3 ROI and what are the figures and Which media sources had highest and lowest cost per purchase in December, and how much were they. How do I calculate them?

View Answer

INSTANT ANSWER

From the perspective of Wierenga&al.(1999) "The Success of Marketing Management Support Systems" , discuss the worth of MMM as a MMSS. How is success determined? In your answer, refer to the article.

View Answer

INSTANT ANSWER

Reflecting on Wedel&Kannan(2016) "Marketing Analytics for Data-Rich Environments", discuss Excel as a tool for analysis in modern data-rich marketing environments.

View Answer

Maria S.