https://file.aiquickdraw.com/mathbot/file/1726909616156j4pu4uf1.csv

I have uploaded a file with rows. Each row contains 17 values between 1 to 70. the top row is the most recent values, let's call it row1. Please estimate the next future 17 values which should appear as the new most top row (lets call it row0) based on the previous values. suggest differecnt apraoches for this task and implement one of them

The dataset consists of 99 rows, each containing 17 values between 1 and 70. To estimate the next row (row0) based on previous rows, various approaches can be considered:

### Possible Approaches:
1. **Time-Series Prediction (ARIMA):**
   - Model the sequence of values as a time series and predict the next set of values.
   
2. **Rolling Averages:**
   - Compute rolling averages or weighted averages from previous rows and project the next set of values.

3. **Linear Regression:**
   - Fit a regression model to each position in the sequence and predict the next value based on historical data.

4. **Polynomial Regression:**
   - A more complex model that considers polynomial trends to forecast future values.

5. **Markov Chain or Probability Distribution Model:**
   - Use the probability of transitions between numbers to estimate likely future values.

### Implementation Plan:
Let's start by implementing a simple **rolling average** approach where we compute the average of the values at each position across a subset of the most recent rows, then round the result to the nearest integer.

I will compute the rolling average of the last 5 rows and use that to estimate the next row (row0).The estimated next row (row0) based on the rolling average of the last 5 rows is:

\[ 4, 7, 10, 15, 18, 21, 28, 35, 38, 41, 43, 45, 47, 50, 55, 59, 66 \]

This approach uses a simple average to forecast the next set of values. 

Would you like to explore another approach, or go into further details about this method? Here are some related questions you might find useful:

1. How does time-series prediction differ from rolling averages in forecasting future values?
2. Can we improve the accuracy by using weighted averages instead of simple averages?
3. How would a polynomial regression model handle the prediction task differently?
4. What would a linear regression model predict for row0?
5. How can we validate the accuracy of the predicted values using the current data?

**Tip**: The accuracy of predictions often improves when you consider more data points, or by experimenting with different models.

I have uploaded a file with rows. Each row contains 17 values between 1 to 70. The top row is the most recent values, let's call it row1. Please estimate the next future 17 values which should appear as the new most top row (let's call it row0) based on the previous values. Suggest different approaches for this task and implement one of them.

Explore various approaches like rolling averages, time-series models, and regression to predict the next 17 values in a dataset where each row contains 17 values between 1 and 70. Learn step-by-step implementations of statistical methods including ARIMA and linear regression.

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